{# # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. -#} {% extends "admin/base.html" %} {% block title %}Confirm Project Name Prohibition for {{ prohibited_project_names.project }}{% endblock %} {% block breadcrumb %}
Are you sure you want to prohibit
{{ prohibited_project_names.project }}
?


Overview
Analytics Zoo
Analytics + AI Platform for Apache Spark and BigDL.
What is Analytics Zoo?
Analytics Zoo makes it easy to build deep learning application on Spark and BigDL, by providing an end-to-end Analytics + AI Platform (including high level pipeline APIs, built-in deep learning models, reference use cases, etc.).
-
- nnframes: native deep learning support in Spark DataFrames and ML Pipelines
- autograd: build custom layer/loss using auto differentiation operations
- Transfer learning: customize pretained model for feature extraction or fine-tuning
-
- Object detection API: high-level API and pretrained models (e.g., SSD and Faster-RCNN) for object detection
- Image classification API: high-level API and pretrained models (e.g., VGG, Inception, ResNet, MobileNet, etc.) for image classification
- Text classification API: high-level API and pre-defined models (using CNN, LSTM, etc.) for text classification
- Recommedation API: high-level API and pre-defined models (e.g., Neural Collaborative Filtering, Wide and Deep Learning, etc.) for recommendation
-
Reference use cases: a collection of end-to-end reference use cases (e.g., anomaly detection, sentiment analysis, fraud detection, image augmentation, object detection, variational autoencoder, etc.)
How to use Analytics Zoo?
-
To get started, please refer to the Python install guide or Scala install guide.
-
For more information, You may refer to the Analytis Zoo document website
-
For additional questions and discussions, you can join the Google User Group (or subscribe to the Mail List)
High level pipeline APIs
Analytics Zoo provides a set of easy-to-use, high level pipeline APIs that natively support Spark DataFrames and ML Pipelines, autograd and custom layer/loss, trasnfer learning, etc.
nnframes
nnframes
provides native deep learning support in Spark DataFrames and ML Pipelines, so that you can easily build complex deep learning pipelines in just a few lines, as illustracted below. (See more details here)
1.Initialize NNContext and load images into DataFrames using NNImageReader
from zoo.common.nncontext import *
from zoo.pipeline.nnframes import *
sc = init_nncontext()
imageDF = NNImageReader.readImages(image_path, sc)
2.Process loaded data using DataFrames transformations
getName = udf(lambda row: ...)
getLabel = udf(lambda name: ...)
df = imageDF.withColumn("name", getName(col("image"))).withColumn("label", getLabel(col('name')))
3.Processing image using built-in feature engineering operations
from zoo.feature.image import *
transformer = RowToImageFeature() -> ImageResize(64, 64) -> ImageChannelNormalize(123.0, 117.0, 104.0) \
-> ImageMatToTensor() -> ImageFeatureToTensor())
4.Define model using Keras-style APIs
from zoo.pipeline.api.keras.layers import *
from zoo.pipeline.api.keras.models import *
model = Sequential().add(Convolution2D(32, 3, 3, activation='relu', input_shape=(1, 28, 28))) \
.add(MaxPooling2D(pool_size=(2, 2))).add(Flatten()).add(Dense(10, activation='softmax')))
5.Train model using Spark ML Pipelines
classifier = NNClassifier(model, CrossEntropyCriterion(),transformer).setLearningRate(0.003) \
.setBatchSize(40).setMaxEpoch(1).setFeaturesCol("image").setCachingSample(False)
nnModel = classifier.fit(df)
autograd
autograd
provides automatic differentiation for math operations, so that you can easily build your own custom loss and layer (in both Python and Scala), as illustracted below. (See more details here)
1.Define custom functions using autograd
from zoo.pipeline.api.autograd import *
def mean_absolute_error(y_true, y_pred):
return mean(abs(y_true - y_pred), axis=1)
def add_one_func(x):
return x + 1.0
2.Define model using Keras-style API and custom Lambda
layer
from zoo.pipeline.api.keras.layers import *
from zoo.pipeline.api.keras.models import *
model = Sequential().add(Dense(1, input_shape=(2,))) \
.add(Lambda(function=add_one_func))
3.Train model with custom loss function
model.compile(optimizer = SGD(), loss = mean_absolute_error)
model.fit(x = ..., y = ...)
Transfer learning
Using the high level transfer learning APIs, you can easily customize pretrained models for feature extraction or fine-tuning. (See more details here)
1.Load an existing model (pretrained in Caffe)
from zoo.pipeline.api.net import *
full_model = Net.load_caffe(def_path, model_path)
2.Remove last few layers
# create a new model by remove layers after pool5/drop_7x7_s1
model = full_model.new_graph(["pool5/drop_7x7_s1"])
3.Freeze first few layers
# freeze layers from input to pool4/3x3_s2 inclusive
model.freeze_up_to(["pool4/3x3_s2"])
4.Add a few new layers
from zoo.pipeline.api.keras.layers import *
from zoo.pipeline.api.keras.models import *
inputs = Input(name="input", shape=(3, 224, 224))
inception = model.to_keras()(inputs)
flatten = Flatten()(inception)
logits = Dense(2)(flatten)
newModel = Model(inputs, logits)
Built-in deep learning models
Analytics Zoo provides several built-in deep learning models that you can use for a variety of problem types, such as object detection, image classification, text classification, recommendation, etc.
Object detection API
Using Analytics Zoo Object Detection API (including a set of pretrained detection models such as SSD and Faster-RCNN), you can easily build your object detection applications (e.g., localizing and identifying multiple objects in images and videos), as illustrated below. (See more details here)
1.Download object detection models in Analytics Zoo
You can download a collection of detection models (pretrained on the PSCAL VOC dataset and COCO dataset) from detection model zoo.
2.Use Object Detection API for off-the-shell inference
from zoo.models.image.objectdetection import *
model = ObjectDetector.load_model(model_path)
image_set = ImageSet.read(img_path, sc)
output = model.predict_image_set(image_set)
Image classification API
Using Analytics Zoo Image Classification API (including a set of pretrained detection models such as VGG, Inception, ResNet, MobileNet, etc.), you can easily build your image classification applications, as illustrated below. (See more details here)
1.Download image classification models in Analytics Zoo
You can download a collection of image classification models (pretrained on the ImageNet dataset) from image classification model zoo
2.Use Image classification API for off-the-shell inference
from zoo.models.image.imageclassification import *
model = ImageClassifier.load_model(model_path)
image_set = ImageSet.read(img_path, sc)
output = model.predict_image_set(image_set)
Text classification API
Analytics Zoo Text Classification API provides a set of pre-defined models (using CNN, LSTM, etc.) for text classifications. (See more details here)
Recommendation API
Analytics Zoo Recommendation API provides a set of pre-defined models (such as Neural Collaborative Filtering, Wide and Deep Learning, etc.) for recommendations. (See more details here)
Reference use cases
Analytics Zoo provides a collection of end-to-end reference use cases, including anomaly detection (for time series data), sentiment analysis, fraud detection, image augmentation, object detection, variational autoencoder, etc. (See more details here)


While anyone could realize a timestamp with any permissionless blockchain by paying the transaction fees, OpenTimestamps public calendar servers are free to use without any registration or API key. A calendar server (e.g. btc-ots.dgi.io) aggregates multiple documents submitted by clients (like this page) and timestamps all of them at the same time using a single blockchain transaction.
While the OpenTimestamps protocol is blockchain agnostic, a timestamp is as reliable as the used blockchain:
It should be obvious, but it is worth mentioning that timestamping (using the OpenTimestamps protocol or any alternative approach):


Starting with version 0.4, Espresso is using Sprockets to serve assets.
To enable and use this feature, simply call assets_url
at app level:
app = EspressoApp.new app.assets_url '/assets' app.assets.append_path 'assets' app.run
Note: make sure you have Sprockets installed. Espresso will require and load it automatically.
Note: Espresso will NOT add any path to Sprockets environment, so it is up to you to do this by using assets.append_path
or assets.prepend_path
.
Note: Sprockets environment will use app root(set via root
at app level)
as base path, so folders containing assets should reside in your app root.
app = EspressoApp.new do assets_url '/assets' assets.append_path 'assets' assets.append_path 'public' end app.run
assets
method can be used to fully setup Sprockets environment:
app = EspressoApp.new do assets_url '/assets' assets.compile = true assets.compress = false assets.js_compressor = :uglifier # etc. end app.run
To access assets inside controllers/templates, use assets
method:
class App < E # ... def some_action assets['application.js'] #=> #<Sprockets::BundledAsset ...> end end
[ contents ↑ ]
Espresso offers some useful helpers aimed to easily create HTML tags:
js_tag :application #=> <script src="/assets/application.js" ... css_tag :application #=> <link href="/assets/application.css" ...
Also helpers for images provided:
- jpg_tag
- jpeg_tag
- png_tag
- gif_tag
- tif_tag
- tiff_tag
- bmp_tag
- svg_tag
- ico_tag
- xpm_tag
- icon_tag
Tag helpers will use assets URL as prefix:
# --- app.rb --- class App < E # ... def index render end end app = EspressoApp.new do assets_url '/public' end app.run # --- view/index.erb --- js_tag :ui # => <script src="/public/ui.js" ... png_tag 'images/header' # => <img src="/public/images/header.png"
If you need to load some asset directly, without assets URL prefix, use :src
option:
js_tag :src => "/jquery" # => <script src="/jquery.js" ... css_tag :src => "http://my.cdn/theme" #=> <link href="http://my.cdn/theme.css" ...
Worth to note that assets mapping can be used without assets being served by Sprockets.
So, when you need to map assets to some URL, so tag helpers will be
automatically prefixed, but you do not need Sprockets,
simply set second
argument to false
when using assets_url
, or its alias - assets_map
:
app = EspressoApp.new do assets_url '/assets', false end
Now assets are mapped to "/assets" and you can use tag helpers without being bothered with Sprockets installation/configuration.
[ contents ↑ ]
Sprockets is doing a great job at loading requirements.
But sometimes you need to load assets from templates rather from Sprockets.
assets_mapper
allow to avoid repetitive path using when loading assets.
Example: - long way:
js_tag 'vendor/jquery' js_tag 'vendor/bootstrap/js/bootstrap' css_tag 'vendor/bootstrap/css/bootstrap' js_tag 'vendor/select2/select2.min' css_tag 'vendor/select2/select2'
Example: - using assets_mapper
assets_mapper :vendor do js_tag 'jquery' cd 'bootstrap' js_tag 'js/bootstrap' css_tag 'css/bootstrap' cd '../select2' js_tag 'select2.min' css_tag 'select2'
[ contents ↑ ]


If link is not clickable please copy and paste above link into your browser's address bar.
Please support the message of the independent media by forwarding this video
to your friends, family and co-workers, post it in your favorite blogs
and forums, share it on Myspace, Facebook, and Twitter, publish it to
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Listen: Blake Shelton releases acoustic version of his party song 'Hell Right'
by Brandy McDonnellNewly Grammy Award-nominated Oklahoma country music superstar Blake Shelton has released an acoustic version of his new party song "Hell Right."
The acoustic version strips away some, but by no means all, of the rowdy party anthem's original trappings to focus more on the Tishomingo resident's buttery country drawl.
As previously reported, the raucous song reunites the Ada native with his deep-voiced pal and "Hillbilly Bone" duet partner Trace Adkins. The music video was lensed in Oklahoma and features the pair throwing a down-home bonfire:
-BAM
Related Photos


Integrates metabolic networks and RNA-seq data to construct condition-specific series of metabolic sub-networks and applies to gene set enrichment analysis (Tran et al. (2018) <doi:10.1093/bioinformatics/bty929>).
| Version: | 1.2.1 |
| Depends: | R (≥ 3.4.0), sybil (≥ 2.0.4), AnnotationDbi (≥ 1.32.3), ape (≥ 3.3), topGO (≥ 2.24.0) |
| Imports: | utils, stats, methods, parallel, grDevices, graphics, Matrix, sys |
| Suggests: | glpkAPI (≥ 1.3.0), clpAPI (≥ 1.2.7), KernSmooth, KEGGREST, survival, ctc, knitr, rmarkdown |
| Published: | 2018-12-12 |
| Author: | Van Du T. Tran [aut, cre], Marco Pagni [aut] |
| Maintainer: | Van Du T. Tran <thuong.tran at sib.swiss> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | metaboGSE citation info |
| Materials: | NEWS |
| CRAN checks: | metaboGSE results |
| Reference manual: | metaboGSE.pdf |
| Vignettes: |
metaboGSE - integrating RNA-seq data and metabolic networks |
| Package source: | metaboGSE_1.2.1.tar.gz |
| Windows binaries: | r-devel: metaboGSE_1.2.1.zip, r-release: metaboGSE_1.2.1.zip, r-oldrel: metaboGSE_1.2.1.zip |
| OS X binaries: | r-release: metaboGSE_1.2.1.tgz, r-oldrel: not available |
| Old sources: | metaboGSE archive |
Please use the canonical form https://CRAN.R-project.org/package=metaboGSE to link to this page.


well, when i took my second trip, I did 5 hits while walking in the forest, and as i was coming up, and walking over a bridge, i drew the lsd molecule on the railing and wrote 'albert hofmann is my father' as a joke. i'm not gonna go into too much detail on the visuals, because they weren't too much different from last time, and i'm sure anyone who's done acid know about 'em already... mainly mandalas and and peoples faces moving around. I watched trainspotting with my sitter (he was somewhat concerned due to the disturbing imagery, but for some reason i've always found that movie to be kind of life affirming and good), but i couldn't really keep track of what was going on. while watching the movie a made a few realizations:
The first was that evolution is a self anihilating concept, in that the species which becomes dominant inevitably destroys itself, allowing the process to start over again.
The second, which i realized as i pet my dog and was overwhelmed
by the vast amount of pure, unconditional love pouring from him, was that we are all one being, experiencing itself for the sheer joy of it, which led me to the third revelation, that the point of life (or at least mine) is to be happy and to make others happy. which is why i can't stand those who disregard others feelings and only persue their own pleasure.
As my sitter left, we talked a little, and i was nearly brought to tears by his kindness in watching me, and allowing me to be myself. I now feel very lucky to have him as a friend, because he has never judged me and he's always supported me in all my decisions.
Later, I went to take a shower. I looked at my body and realized how ape like humans really are, and i realized that as much as we revel in our physical achievements, and our physical form, we are, as a people, ashamed of our simian heritage, although many of our postures are those of apes, and squatting on my feet, i could almost feel a tail extending from my spine...
overall, it was a very good day, and i hope to repeat the experience before too long, but those 5 hits were the last of the 10 that i got in october and i don't have any money at the moment, so i'll probably end up taking another 3 month stint of sobriety...
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


--- layout: default title: Leadership Council description: Every month, we hold an open Leadership Council meeting at Code for San Francisco to discuss new ideas and ways to make the hack night better. Anyone is welcome to join! ---
Every month, we hold an open Leadership Council meeting at Code for San Francisco to discuss new ideas and ways to make the hack night better. Anyone is welcome to join!
| Meeting # | Date | Minutes |
|---|---|---|
| {{ meeting.id }} {% if next_meeting %} Next meeting {% endif %} | {{ meeting.date | date: "%b %d, %Y" }} | {% if next_meeting %}Agenda{% else %}Minutes{% endif %} |


#include <stdint.h>
#include <stdlib.h>
#include <stdbool.h>
#include <stdio.h>
#include <string.h>
#include <errno.h>
#include "types.h"
#include "memory.h"
#include "log.h"
#include <sys/types.h>
#include <sys/stat.h>
#include <fcntl.h>
#include <unistd.h>
Go to the source code of this file.
|
| #define | OFF_T int32_t |
| |
| #define | FTELL ftell |
| |
| #define | FSEEK fseek |
| |
| #define | STAT stat /* always stat64 on Linux kernel 2.4+ */ |
| |
| #define | MODE 0777 |
| |
| #define | OFLAG O_RDWR | O_CREAT | O_EXCL |
| |
| #define | CLOSE close |
| |
| #define | FSCANF fscanf |
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| #define | OPEN(handle, filename, flag, mode) (((*handle = open(filename, flag, mode)) == -1) ? errno : false) |
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| #define | FOPEN(file, filename, mode) (((*file = fopen(filename, mode)) == NULL) ? errno : false) |
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| OFF_T | file_find_size (const file_t *file) |
| | Find the system storage size of a file. More...
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| |
| bool | file_read (file_t *file, const OFF_T offset, const OFF_T count, const bool change_indicator) |
| | Read a block of data from system storage and store it into the file buffer. More...
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| |
| bool | file_read_line (file_t *file, const bool change_indicator) |
| | Read a line from file. More...
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| |
| bool | file_write (file_t *file, const OFF_T offset, const OFF_T count, const bool change_indicator) |
| | Flush block of data from file buffer into system storage. More...
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| |
| bool | file_replace_buffer (file_t *file, data_t *data) |
| | Write block of data into file buffer. More...
|
| |
| void | file_close (file_t *file) |
| | Close open file and clean up memory. More...
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| |
| bool | file_open (file_t **file, char *path) |
| | Open a file and initialize struct values. More...
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| |
| bool | file_create (const char *filename) |
| | Create a new file. More...
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| |
| bool | file_seek (file_t *file, const OFF_T offset) |
| | Move file indicator. More...
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| |
◆ CLOSE
◆ FOPEN
| #define FOPEN |
( |
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file, |
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filename, |
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mode |
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) |
| (((*file = fopen(filename, mode)) == NULL) ? errno : false) |
◆ FSCANF
◆ FSEEK
◆ FTELL
◆ MODE
◆ OFF_T
◆ OFLAG
| #define OFLAG O_RDWR | O_CREAT | O_EXCL |
◆ OPEN
| #define OPEN |
( |
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handle, |
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filename, |
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flag, |
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mode |
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) |
| (((*handle = open(filename, flag, mode)) == -1) ? errno : false) |
◆ STAT
| #define STAT stat /* always stat64 on Linux kernel 2.4+ */ |
◆ file_t
Data used to work with files.
◆ file_close()
| void file_close |
( |
file_t * |
file | ) |
|
Close open file and clean up memory.
- Parameters
-
| file | reference to file struct |
◆ file_create()
| bool file_create |
( |
const char * |
filename | ) |
|
Create a new file.
The new file should not exist. Also, the file should be at an existing directory.
- Parameters
-
| filename | relative or absolute path to the new file |
- Returns
- bool true if successful, false if failed
◆ file_find_size()
Find the system storage size of a file.
- Parameters
-
| file | reference to file struct |
- Returns
- OFF_T file size
◆ file_open()
| bool file_open |
( |
file_t ** |
file, |
|
|
char * |
path |
|
) |
| |
Open a file and initialize struct values.
The file should exist.
- Parameters
-
| file | reference to pointer where file struct is located |
| path | string to file path |
- Returns
- bool true if successful, false if failed
◆ file_read()
| bool file_read |
( |
file_t * |
file, |
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const OFF_T |
offset, |
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count, |
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change_indicator |
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Read a block of data from system storage and store it into the file buffer.
- Parameters
-
| file | reference to file struct |
| offset | position from start of file |
| count | amount of bytes to be read |
| change_indicator | should file cursor stay changed after reading from file? |
- Returns
- bool true if successful, false if failed
◆ file_read_line()
| bool file_read_line |
( |
file_t * |
file, |
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const bool |
change_indicator |
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) |
| |
Read a line from file.
- Parameters
-
| file | reference to file struct |
| change_indicator | should file cursor stay changed after reading from file? |
- Returns
- bool true if successful, false if failed
◆ file_replace_buffer()
Write block of data into file buffer.
The file buffer will be replaced.
- Parameters
-
| file | reference to file struct |
| data | block of data to replace file buffer |
◆ file_seek()
Move file indicator.
- Parameters
-
| file | reference to file struct |
| offset | position from start of file |
- Returns
- bool true if successful, false if failed
◆ file_write()
| bool file_write |
( |
file_t * |
file, |
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const OFF_T |
offset, |
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const OFF_T |
count, |
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const bool |
change_indicator |
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) |
| |
Flush block of data from file buffer into system storage.
- Parameters
-
| file | reference to file struct |
| offset | position from start of file |
| count | amount of bytes to be write |
| change_indicator | should file cursor stay changed after writing to file? |
- Returns
- bool true if successful, false if failed


Load previous results
Status:
Output files will be stored on chromEvol server for one month
User inputs:
Chromevol results:


About
Work
Contact
Hey, We are Nzube and Morris
Card title
Here is Our PortFolio Site.
Go somewhere
Card title
Here is Our PortFolio Site.
Go somewhere
Nzube's Github
Morris's Github


Transfer Wizard
Generate optimal substitutions based upon your budget and current squad.
{% if request.session.username or request.session.team_name %}
{% include 'transfer_sim_form.html' %}
{% include "current_squad_table.html" %}
You need to be connected to your squad to use this feature. You can connect to your squad by clicking 'Connect Squad' at the top of the page.
{% endif %}


--- title: Contributors permalink: /contributors/ layout: layouts/home.html eleventyNavigation: key: Contributors order: 3 ---
Contributors are ordered from A to Z.


001/* 002// This software is subject to the terms of the Eclipse Public License v1.0 003// Agreement, available at the following URL: 004// http://www.eclipse.org/legal/epl-v10.html. 005// You must accept the terms of that agreement to use this software. 006// 007// Copyright (C) 2004-2005 TONBELLER AG 008// Copyright (C) 2006-2011 Pentaho and others 009// All Rights Reserved. 010*/ 011package mondrian.spi; 012 013/** 014 * An SPI to format the cell values. 015 * 016 *
The user registers the CellFormatter's 017 * full class name as an attribute of a Measure in the schema file. 018 * A single instance of the CellFormatter is created for the Measure.
 019 * 020 *
Since CellFormatters will 021 * be used to format different Measures in different ways, you must implement 022 * the equals and hashCode methods so that 023 * the different CellFormatters are not treated as being the same in 024 * a {@link java.util.Collection}. 025 */ 026public interface CellFormatter { 027 /** 028 * Formats a cell value. 029 * 030 * @param value Cell value 031 * @return the formatted value 032 */ 033 String formatCell(Object value); 034} 035 036// End CellFormatter.java


| Created: | 6/26/2020 3:15:33 PM |
| Modified: | 6/26/2020 3:15:33 PM |
| Project: | |
| Advanced: |
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| isFinalSpecialization: | 0 |
| Object | Type | Connection | Direction | Notes |
| «view» current_contracts_view | View | Dependency | From | |
| «view» current_contracts_view | View | Dependency | From |


Intended audience: users, HTML coders, script developers (PHP, JSP, etc.), CSS coders, schema developers (DTDs, XML Schema, RelaxNG, etc.), XSLT developers, Web project managers, and anyone who is new to internationalization and needs guidance on topics to consider and ways to get into the material on the site. yyy adapt this to describe the intended reader of the article.
What is a floating time and how do I handle floating times in my Web application?
A floating time or a floating date is a time value that isn't tied to a specific time zone. Applications that work with floating times need to avoid pitfalls that can arise from implicit conversion to incremental time values or the improper use of time zones when displaying or processing a floating time value.
The Working with Timezones WG Note says:
Some observed time values are not related to a specific moment in incremental time. Instead, they need to be combined with local information to determine a range of acceptable incremental time values. We refer to these sorts of time values as "floating times" because they are not fixed to a specific incremental time value. Floating times are not attached and should never be attached to a particular time zone.
That is, a floating time usually refers to a range of possible time values that share a specific relationship to the defined moment in time that the floating value represents. Examples of floating times include concepts such as birth date, starting or ending dates for a worldwide event, holidays, or publication dates.
For example, consider the publication date of a document—let's say a specific issue of an online newspaper. On 30 April 2017 this newspaper published a Sunday edition. And indeed, the newspaper might have declared the date like this in HTML:
This seems unambiguous. Yet for some reason when Martina, who is in Buenos Aires, Argentina,
opens the Web site, she sees "Saturday edition" and "29 April 2017" as the date for her copy. Problems such as this
can arise if Web developers or content authors do not treat the publication date as a floating time value. For example,
the JavaScript Date
object is a form of incremental time: it represents
the number of milliseconds since an epoch date.
In the case of JavaScript, the epoch data is the same as that used by Unix, the Java programming language, and many other systems:
it's defined as midnight, January 1, 1970 in the UTC (Universal Coordinated Time) time zone. So for Martina's
newspaper, the value in the HTML document might be converted in JavaScript to a Date
object
with the value:<PHONE_NUMBER>000 (in milliseconds since the epoch).
Suppose your element myPubDateElement
contained the value above (2017-04-30).
You'd expect the element date_target
contain a string representing that date.
However, if you live in a time zone west of UTC (such as Martina, in the America/Buenos_Aires
time zone),
you'll get a surprise. It says:
The problem here is that many of the Date
methods in JavaScript are sensitive to the local system's time zone and they try to present the value using local time zone rules. Because the time of day was not
specified, the time is treated as midnight
, so anyone displaying the underlying value in a time zone following UTC will naturally see the previous day.
In the case of a system running in the America/Buenos_Aires
time zone, which has an offset from UTC of either -3 hours or -2 hours (depending on whether or not daylight savings time is in effect) the value presented to the user from the JavaScript is incorrect because the the time
portion
of the publication date is zeroed out. Subtracting two or three hours from the Date
object results in a presentation string that is on the previous day. That day might be in the wrong month or even the wrong year.
Because the local interpretation of a given date depends on the local time—that is, it depends on the local calendar, clock, and time zone rules—the range of incremental times that might be described as 2017-04-30 turns out to span as many as fifty hours. The earliest time that can be called "30 April 2017" starts in Kiribati in the South Pacific, some 14 hours before midnight on 30 April 2017 occurs in UTC. The last moment that can be called part of "30 April 2017" occurs just before midnight of "1 May 2017" on the island of Midway's time zone, some 11 hours after "30 April 2017" has ended in UTC (there is an even later zone, but it is uninhabited). Depending on the time zone used to create and then later to display an incremental time value, the same floating date value could appear to be as much as two days off.
That's because, while a floating time is not tied to a specific time zone, any incremental time values depend on time zone for their display and processing. Since data formats for time values in both server-side (such as Java or PHP) and client-side languages (such as JavaScript) are always incremental times, this can lead to problems such as Martina's mysterious newspaper publication date.
One way to work around this it to always use the UTC time zone for processing floating time values. Developers have to be careful to convert time values into incremental time objects using an offset of zero and segregate code that deals with floating times from more-normal time values such as time stamps.
Another way that floating times are used is in the aggregation of data. For example, suppose you are building an application that keeps track of the number of downloads a user makes. You can record each download using a timestamp (an incremental time value). That might look like this:
When your application wants to aggregate statistics, the use of incremental times
to represent the aggregated data could become a problem. Suppose you want to
accumulate user statistics, such as total downloads, on a daily basis.
The timestamp in the example above might fall on October 2, 2013 for that customer.
In this case, if the time zone were America/Los_Angeles
as
shown in the record, it would not! Here's what the accumulated record might look like:
In this case, you want to use local time rules, including the time zone,
in order to compute which floating date the download should accumulate to. But you want to use floating time
rules to read and write the accumulated data record. That way the statistics remain the same
for a given date, even if the user's time zone has changed in the interim. For example,
if the customer moves to the Europe/Paris
time zone, the
number of downloads on 2013-10-01
should remain the same, even though the
accumulation rules might be different now than they were previously.
Getting started? Time & date: Essential concepts
Related links, Developing specifications


Common constraint programming problems
Below are the problems which I have implemented in at least two Constraint Programming systems. For more about these systems see the following links. The number shows the (approximate) number of models implemented in the system.
- AIMMS+CP, see my AIMMS+CP page (35 models)
- AMPL, see my AMPL page (272 models) [Note: Some are plain IP models]
- B-Prolog, see my B-Prolog page (203 models)
- Choco, see my Choco page (15 models)
- Choco3 (not compatible with Choco2), see my Choco3 page (87 models)
- Comet, see my Comet page (155 models)
- CPMPy, see my cpmpy page (308 models)
- ECLiPSe CLP, see my ECLiPSe page (200 models)
- Essence'/Savile Row, see my Essence'/Savile Row page (67 models)
- Essence'/Tailor, see my Essence'/Tailor page (22 models)
- Gecode, see my Gecode page (145 models)
- Gecode/R, see my Gecode/R page (25 models)
- OR or-tools/C#, see my OR-tools page (107 models)
- OR-tools/Java, see my OR-tools page (34 models)
- OR-tools/Python, see my OR-tools page (131 models)
- OR-tools/Python CP-SAT, see my OR-tools page (125 models)
- JaCoP, see my JaCoP page (14 models)
- JaCoP/Scala, see my JaCoP/Scala page (34 models)
- Java JSR-331, see my JSR-331 page (32 models)
- Julia ConstraintSolver.jl, see my Julia ConstraintSolver.jl (124 models)
- MiniZinc, see my MiniZinc page(1138 models)
- Numberjack, see my Numberjack page (31 models)
- OscaR, see my OscaR page (Scala in OR) (116 models)
- Picat, see my Picat page (1919 models) [Note: Not all are CP models]
- SICStus Prolog, see my SICStus Prolog page (148 models)
- SWI-Prolog, see my SWI-Prolog page (254 models)
- Zinc, see my Zinc page (29 models)
- Z3Py, see my Z3/Z3Py page (243 models)
- Answer Set Programming (Potassco Clingo), see my Answer Set Programming page (79 encodings)
- Answer Set Programming (Potassco Clingo v4), see my Answer Set Programming page (84 encodings)
Notes:
- Note 1: This is an autogenerated file so some models may be missing, and there may be some other peculiarities.
- Note 2: I have included my Answer Set Programming encodings here as well, even if these are not strictly Constraint Programming (though it is a related paradigms and might be interesting to compare).
- Note 3: Since some of the systems are general purpose programming languages (and I tend to play with other aspects than CP when learning a new programming language), some of the shown models/programs do not use a CP approach. This applies especially to Picat.
Currently there are 1112 problems implemented in at least 2 CP systems. There are 4741 implemented models. (Total implemented models, including those not showed here, is about 6176.)
Occurrences of problems
Here is the distribution of the number of implementations:
- 30: 2 (cumulative: 2)
- 29: 2 (cumulative: 4)
- 28: 2 (cumulative: 6)
- 26: 2 (cumulative: 8)
- 25: 1 (cumulative: 9)
- 24: 1 (cumulative: 10)
- 23: 1 (cumulative: 11)
- 22: 4 (cumulative: 15)
- 21: 7 (cumulative: 22)
- 20: 5 (cumulative: 27)
- 19: 8 (cumulative: 35)
- 18: 10 (cumulative: 45)
- 17: 8 (cumulative: 53)
- 16: 8 (cumulative: 61)
- 15: 6 (cumulative: 67)
- 14: 4 (cumulative: 71)
- 13: 11 (cumulative: 82)
- 12: 11 (cumulative: 93)
- 11: 11 (cumulative: 104)
- 10: 21 (cumulative: 125)
- 9: 17 (cumulative: 142)
- 8: 16 (cumulative: 158)
- 7: 22 (cumulative: 180)
- 6: 27 (cumulative: 207)
- 5: 35 (cumulative: 242)
- 4: 45 (cumulative: 287)
- 3: 158 (cumulative: 445)
- 2: 667 (cumulative: 1112)
- 1: 1435 (cumulative: 2547)
Learning problems
The following (about 207) problems are often the first problems that is modelled when learning a new Constraint Programming system. Here are shown those that has been implemented in at least 6 systems:
Common problem
Problem: 12_pack_problem (2)
Problem: 17_b (2)
Problem: 18_hole_golf A golf (i.e. shortest program) version of random 18-hole golf generation. Length: 76 chars. [Puzzle] (3)
Problem: 1d_rubiks_cube 1D Rubik's cube (including GAP code for solving the problem using group theory) [Puzzle] (4)
Problem: 1rm Weight training: Calculations of 1RM and comparing reps x weights. [Nonlinear/Var float] (3)
Problem: 2012_cmo_problem (3)
Problem: 225_divisor Smallest number divisible by 225 that consists of all 1s and 0s [Puzzle] (2)
Problem: 3_coins 3 coins (THT), in exactly 3 flips make HHH or TTT [Puzzle] (3)
Problem: 3_jugs 3 jugs problem (as shortest path problem) [Puzzle] (9)
Problem: 3_jugs2 3 jugs problem (using shortest_path_model. [Puzzle] (3)
Problem: 3_jugs_mip (3)
Problem: 3_jugs_regular (7)
Problem: 3sum 3SUM problem (general approach) [Combinatorial] (5)
Problem: 4x4_grid_equations (2)
Problem: 50_puzzle Fifty puzzle [Martin Chlond IP] (6)
Problem: 5x5_puzzle (5)
Problem: 99_bottles_of_beer 99 bottles of beer (Rosetta code) [Misc] (2)
Problem: aaa_bbb_ccc AAA+BBB+CCC=BAAC (Mind Your Decisions problem) [Puzzle] (2)
Problem: abbots_puzzle (10)
Problem: abbott The Abbott's Window [Martin Chlond IP] (3)
Problem: abc_endview ABC End View grid puzzle (a.k.a. "Easy as ABC", "Last Man Standing") [Puzzle] (3)
Problem: a_card_trick_1 (2)
Problem: ackermann (2)
Problem: added_corner Added corner puzzle [Puzzle] (13)
Problem: adjacency_matrix_from_degrees (2)
Problem: age_changing Age changing (Enigma 1224) [Puzzle] (5)
Problem: ages Ages problem from Tony Hurlimann [Nonlinear/Var float] (2)
Problem: ages2 (2)
Problem: agprice Agricultural pricing (Willams: "Model building in MP") [Nonlinear/Var float] (3)
Problem: a_league_of_their_own_enigma_1217 A league of their own (#1217) [Puzzle] (2)
Problem: alldifferent_consecutive_values alldifferent_consecutive_values [Global constraint] (3)
Problem: alldifferent_cst alldifferent_cst, and alldifferent_cst using multiplication instead of addition [Global constraint] (9)
Problem: all_different_except_0 (26)
Problem: alldifferentexcept0 (2)
Problem: alldifferent_explain alldifferent with "explanations" (with a set of duplicated values) [Global constraint] (3)
Problem: alldifferent_interval alldifferent_modulo, all values modulo k shall be different [Global constraint] (2)
Problem: alldifferent_modulo alldifferent_modulo, all values modulo k shall be different [Global constraint] (9)
Problem: alldifferent_on_intersection alldifferent_on_intersection [Global constraint] (7)
Problem: all_different_pairs defines all_different_pairs, increasing_pairs, decreasing_pairs, and the function pairs [Global constraint] (4)
Problem: alldifferent_partition alldifferent_partition [Global constraint] (2)
Problem: all_different_reif (2)
Problem: alldifferent_same_value alldifferent_same_value [Global constraint] (2)
Problem: alldifferent_soft alldifferent_soft (alldifferent_soft_ctr and alldifferent_soft_var) [Global constraint] (2)
Problem: all_differ_from_at_least_k_pos all_differ_from_at_least_k_pos, all rows in a matrix has values that differs in at least k positions [Global constraint] (9)
Problem: all_equal (7)
Problem: all_interval All interval problem (series), (CSPLib problem 7) [Combinatorial] (22)
Problem: allinterval All interval problem (series), (CSPLib problem 7) [Combinatorial] (3)
Problem: all_min_dist all_min_dist, all values must have a minimum distance to each other [Global constraint] (9)
Problem: allocating_developments Allocating developments [Puzzle] (2)
Problem: allpartitions (7)
Problem: all_paths_graph (All) paths from a graph presentation (cf message_sending. [Combinatorial] (2)
Problem: allperm allperm, ensures that the first rows in a matrix is lexically less than all permutation of all other rows [Global constraint] (2)
Problem: alpha (3)
Problem: alphametic (10)
Problem: alphametic3 (2)
Problem: among (11)
Problem: among_diff_0 among_diff_0, number of values different from 0 [Global constraint] (2)
Problem: among_interval among_interval, number of values in a certain interval [Global constraint] (2)
Problem: among_low_up among_low_up, the number values in an array matched another array shoule be constrained to low and up [Global constraint] (2)
Problem: among_modulo among_modulo, the number values in an array where a value modulo quotient = remainder [Global constraint] (2)
Problem: among_seq among_seq [Global constraint] (9)
Problem: and and, generalized and (array) [Global constraint] (2)
Problem: anniversaries Anniversaries (Logic4Fun) [Puzzle] (2)
Problem: another_kind_of_magic_square (2)
Problem: antisymmetric Antisymmetric relation (matrix) [Misc] (2)
Problem: appointment_scheduling (7)
Problem: appointment_scheduling_set A set based approach to the appoiintment scheduling problem (see above). [Combinatorial] (3)
Problem: a_puzzle (12)
Problem: arbitrage_loops Arbitrage loops (currencies)
[Nonlinear/Var float] (2)
Problem: archery_puzzle Archery puzzle (Sam Loyd) [Puzzle] (5)
Problem: arch_friends Arch friends puzzle (Dell Logic Puzzles) [Puzzle] (15)
Problem: are_you_the_one Are you the one? problem [Puzzle] (2)
Problem: argmax Predicates argmax_gt, argmax_ge, argmin_lt, argmin_le. E.g. argmax_gt(pos, x): pos is the position in array x for the maximum value. The other predicates is defined accordingly. [Misc] (3)
Problem: arith arith, enforces that all values in an array is RELOP (equal, not equal, less than, etc) some VALUE [Global constraint] (4)
Problem: arithmetic_ring Arithmetic ring problem [Puzzle] (2)
Problem: arith_or arith_or [Global constraint] (2)
Problem: arith_sliding arith_sliding, all sliding sums from 1..j must satisfy RELOP VALUE [Global constraint] (2)
Problem: a_round_of_golf A round of golf puzzle (Dell Logic Puzzles) [Puzzle] (19)
Problem: arrow (2)
Problem: artificial_intelligence (2)
Problem: assign_and_counts assign_and_counts [Global constraint] (2)
Problem: assign_and_nvalues assign_and_nvalues [Global constraint] (2)
Problem: assignment Assignment problem (Winston) [OR] (22)
Problem: assignment2 Assignment problem (Winston's swimming team example) [OR] (3)
Problem: assignment3 Assigment problem (Winston, celebreties on an island) [OR] (3)
Problem: assignment6 Assigment problem (GLPK:s example assign.mod) [OR] (2)
Problem: atleast_nvalue atleast_nvalue, at least NVAL values are different in an array [Global constraint] (2)
Problem: atmost_nvalue atmost_nvalue, at most NVAL values are different in an array [Global constraint] (2)
Problem: atmost_test (3)
Problem: atom_smasher Digital Atom Smasher. Alphametic problem: sqrt(ATOM) = A + TO + M [Puzzle] (2)
Problem: autoref Auto referential puzzle [Puzzle] (4)
Problem: average_avoiding (2)
Problem: averbach_1.2 Example 1.2 in Averbach & Chein "Problem Solving Through Recreational Mathematics" [Puzzle] (6)
Problem: averbach_1_2 (3)
Problem: averbach_1.3 Example 1.3 in Averbach & Chein "Problem Solving Through Recreational Mathematics" [Puzzle] (6)
Problem: averbach_1.4 Example 1.4 in Averbach & Chein "Problem Solving Through Recreational Mathematics" [Puzzle] (7)
Problem: babysitting Babysitting puzzle (Dell Logic Puzzles) [Puzzle] (10)
Problem: balance balance, difference between the least and largest number of occurrences in an array [Global constraint] (2)
Problem: balanced_brackets Generate balanced brackets [Combinatorial] (4)
Problem: balanced_matrix Balanced matrix [Combinatorial] (2)
Problem: balance_interval balance_interval, difference between the least and largest number of occurrences in intervals in an array [Global constraint] (2)
Problem: balance_modulo balance_modulo, difference between the least and largest number of occurrences of the equivalience classes modulo an integer [Global constraint] (2)
Problem: balance_partition balance_partition, difference between the least and largest number of occurrences in partitions [Global constraint] (2)
Problem: bales_of_hay Bales of hay puzzle [Puzzle] (13)
Problem: bananas Bananas problem. [Puzzle] (5)
Problem: bank_card Bank card puzzle [Puzzle] (2)
Problem: barrels Barrels problem (From September Magic Contest 2014) [Puzzle] (2)
Problem: before_and_after Before and After (Logic4Fun) [Puzzle] (2)
Problem: bertrand_russell_puzzle Bertrand Russell puzzle [Puzzle] (2)
Problem: best_host Best host problem (from PuzzlOR) [OR] (4)
Problem: best_shuffle (2)
Problem: between_min_max between_min_max, a specific number is between the minimum and maximum value of an array [Global constraint] (2)
Problem: binary_puzzle Binary puzzle [Puzzle] (2)
Problem: binary_sudoku Binary Sudoku [Puzzle] (2)
Problem: binary_tree Binary tree [Global constraint] (2)
Problem: binero Binero grid puzzle (from Scampi) (cf (2)
Problem: binoxxo Binoxxo grid puzzle (cf (2)
Problem: bin_packing (8)
Problem: bin_packing2 Bin packing (different from the one above) [Combinatorial] (7)
Problem: birthday_coins (2)
Problem: birthday_paradox Birthday paradox (birthday problem) [Nonlinear/Var float] (2)
Problem: birthdays_2010 A simple birthday puzzle of my own, based on a coincidence of my and my brother's birth years. [Puzzle] (2)
Problem: birthdays_coins Tommy's Birthday Coins [Martin Chlond IP] (3)
Problem: bit_patterns (2)
Problem: bit_vector1 A small bit vector problem [Misc] (2)
Problem: blending Blending problem (OPL) [Nonlinear/Var float] (6)
Problem: blending_problem Blending problem [OR] (2)
Problem: blueberry_muffins Blueberry muffins problem (Brown Buffalo Logic Puzzles) [Puzzle] (2)
Problem: bobsledders_puzzle Bobsledders puzzle [Puzzle] (2)
Problem: book_buy Book buy puzzle [Martin Chlond IP] (5)
Problem: book_discount Book discount problem [Martin Chlond IP] (2)
Problem: bowls_and_oranges (5)
Problem: box Design a box [Nonlinear/Var float] (4)
Problem: bplan (2)
Problem: bpp Bin packing (GLPK example, but not using the "z heuristic") [Combinatorial] (2)
Problem: breaking_news Breaking news puzzle (Dell Logic Puzzles) [Puzzle] (12)
Problem: bridge_and_torch_problem Bridge and torch problem, crossing a bridge with a torch (a.k.a. The Midnight Train, and Dangerous crossing).
[Puzzle] (2)
Problem: bridges_to_somewhere Bridges to Somewhere (from PuzzlOR) [OR] (2)
Problem: broken_weights Broken weights problem [Puzzle] (17)
Problem: buckets Buckets problem (minimizing differences of masses in four buckets) [Puzzle] (2)
Problem: build_a_house (4)
Problem: building_a_house Simple scheduling problem: building a house (from OPL) [OR] (7)
Problem: building_blocks Building blocks (Dell Logic Puzzles) [Puzzle] (8)
Problem: building_blocks2 (2)
Problem: building_design Building design [Nonlinear/Var float] (2)
Problem: bus Bus puzzle (from rec.puzzles FAQ) [Puzzle] (2)
Problem: bus_schedule (17)
Problem: busschedule Bus scheduling (Taha) [OR] (4)
Problem: bus_scheduling_csplib Bus driver scheduling (CSPLib problem 22). Data files: [OR] (6)
Problem: calculs_d_enfer Calculs d'enfer puzzle (from the NCL manual) [Puzzle] (15)
Problem: calvin_puzzle Calvin puzzle [Puzzle] (3)
Problem: candies Candies problem (from HackerRank) [Puzzle] (4)
Problem: capital_budget (2)
Problem: capital_budget2 Capital Budget (Winston) [OR] (4)
Problem: car Car sequencing problem (OPL) [Combinatorial] (8)
Problem: cardinality_atleast cardinality_atleast [Global constraint] (2)
Problem: cardinality_atmost cardinality_atmost [Global constraint] (2)
Problem: cardinality_atmost_partition cardinality_atmost_partition [Global constraint] (2)
Problem: car_painting Car painting problem (from SAS/OR User's Guide) [Combinatorial] (2)
Problem: carpool_fairness Carpool fairness
[Combinatorial] (2)
Problem: car_talk_odometer Odometer problem from Cat Talk [Puzzle] (2)
Problem: cashier_change Cashier change problem (coin problem) [Puzzle] (2)
Problem: catalan_numbers Catalan numbers [Misc] (2)
Problem: celsius_fahrenheit Conversion from/to degree Celsius to/from degree Fahrenheit [Nonlinear/Var float] (3)
Problem: chain_of_primes Chain of primes (#1216) [Puzzle] (2)
Problem: chandelier_balancing Chandelier balancing (PuzzlOR) [Puzzle] (2)
Problem: change circular change, number of changes in an array [Global constraint] (2)
Problem: change_pair change_pair [Global constraint] (2)
Problem: change_partition change_partition [Global constraint] (2)
Problem: changepoint_detection Changepoint detection, mix float and integer [Puzzle] (3)
Problem: changes (5)
Problem: checker_puzzle (2)
Problem: chess_set Chess set problem (XPress) [OR] (5)
Problem: chinese_remainder_problem Chinese remainder problem [Misc] (2)
Problem: choose_your_crew Choose your crew (from PuzzlOR) [OR] (2)
Problem: choosing_teams (2)
Problem: circling_squares Circling the Squares (Dudeney) [Nonlinear/Var float] (10)
Problem: circuittest circuit [Global constraint] (16)
Problem: circuit_path Extracting the path from a circuit [Global constraint] (3)
Problem: circuit_test circuit [Global constraint] (4)
Problem: circular circular: ensure that an array of length m
with domain 1..n
are circular ordered (and can start on any value of 1..n
). [Global constraint] (2)
Problem: circular_change circular change, number of changes in an array (as change but with wrapping around the corner) [Global constraint] (2)
Problem: circular_except_0 circular: ensure that an array of length m
with domain 1..5
are circular ordered (and can start on any value of 1..5
), and supports dummy values (= 0). [Global constraint] (2)
Problem: classify_department_employees Classify Department Employees (Decision Management Community problem) [OR] (2)
Problem: climbing_stairs Climbing stairs [Puzzle] (2)
Problem: clique clique [Global constraint] (10)
Problem: clock_triplet (4)
Problem: clocktriplet Clock Triplets [Martin Gardner] (6)
Problem: coins Coin puzzle [Martin Chlond IP] (3)
Problem: coins2 (2)
Problem: coins3 Minimum mumber of coins that allows one to pay exactly any amount smaller than one Euro [Puzzle] (19)
Problem: coins_41_58 Minimize number of coins - with the same amount of the different denominations - that sums to 41.58 GBP [Puzzle] (2)
Problem: coins_grid Coins Grid (Tony Hurlimann) [Puzzle] (29)
Problem: coins_of_the_realm (2)
Problem: coins_problem Minimum mumber of coins that allows one to pay exactly any amount smaller than one Euro (alternative solution based on OPL code) [Puzzle] (2)
Problem: color Map coloring, Martin Gardner's coloring problem (BProlog) [Martin Gardner] (2)
Problem: coloring (2)
Problem: coloring_cp_sat (2)
Problem: coloring_ip Map coloring, integer programming (inspired by the GLPK model color.mod) [OR] (6)
Problem: color_simple Simple coloring of a map (Murty) [Combinatorial] (3)
Problem: col_sum_puzzle Find out values in a matrix, given column and row sums and some hints. [Puzzle] (2)
Problem: combination_locks Combination locks (PuzzlOR) [Puzzle] (2)
Problem: combinatorial_auction Simple combinatorial auction problem (compare with the set covering/set partition problem in (13)
Problem: combinatorialauction Simple combinatorial auction problem (compare with the set covering/set partition problem in (7)
Problem: common common, also used_by [Global constraint] (2)
Problem: common_interval common_interval [Global constraint] (2)
Problem: common_modulo common_modulo [Global constraint] (2)
Problem: common_partition common_partition [Global constraint] (2)
Problem: company_competition (Christmas) Company Competition Problem: Mixing teams [OR] (2)
Problem: cond_lex_cost cond_lex_cost [Global constraint] (2)
Problem: cond_lex_less cond_lex_less, cond_lex_lesseq, cond_lex_greater, cond_lex_greatereq [Global constraint] (2)
Problem: conference Conference problem (from "Constraint Programming with Alice") [Combinatorial] (2)
Problem: config Configuration problem (from OPL) [Combinatorial] (2)
Problem: congress Congress puzzle (from XPress Mosel) [Puzzle] (2)
Problem: consecutive_digits Consecutive digits [Martin Gardner] (2)
Problem: consecutive_integer_partition_problem (2)
Problem: consecutive_values consecutive_values [Global constraint] (2)
Problem: constraint Optimizing a constraint (Williams) [OR] (2)
Problem: contains_array contains ("in" for arrays) [Global constraint] (2)
Problem: contiguity_mip Contiguity constraint (MIP, using floats) [OR] (2)
Problem: contiguity_regular global_contiguity (using regular constraint) [Global constraint] (7)
Problem: contracting_costs (6)
Problem: controversy_about_the_weekday Controversy about the weekday [Puzzle] (2)
Problem: cookie_bake_off Cookie bake off (PuzzlOr) [Puzzle] (3)
Problem: cookie_bake_off2 Cookie bake off (PuzzlOr) [Nonlinear/Var float] (2)
Problem: cookie_monster_problem Cookie Monster Problem (from Richard Green The Cookie Monster Problem at Google+) [Combinatorial] (2)
Problem: correspondence correspondence [Global constraint] (2)
Problem: costas_array Costas array (based on Barry O'Sullivan's model) [Combinatorial] (13)
Problem: count_ctr (2)
Problem: counts counts [Global constraint] (2)
Problem: covering_opl (16)
Problem: cp_utils (2)
Problem: crew Crew scheduling (Gecode) [OR] (16)
Problem: crew_overlapping_flights Crew scheduling with overlapping flights (StackOverflow) [OR] (2)
Problem: critical_path1 Critical Path (Winston) [OR] (3)
Problem: crossbar Crossbar problem (Prolog benchmark problem) [OR] (3)
Problem: crossfigure Crossfigure problem (CSPLib problem 21) [Puzzle] (6)
Problem: crossword Crossword solving (standard constraint programming example) [Puzzle] (10)
Problem: crossword2 Crossword solving (standard constraint programming example), more general approach [Puzzle] (14)
Problem: crowd The crowded board [Martin Chlond IP] (3)
Problem: crypta crypta, alphametic problem (standard Prolog benchmark) [Puzzle] (15)
Problem: crypto crypto, alphametic problem (standard Prolog benchmark), constraint programming model [Puzzle] (15)
Problem: crypt_reversed (2)
Problem: crystal_maze Crystal maze problem [Puzzle] (2)
Problem: cube_sum Sum a number with the minimum number of different cubes [Puzzle] (2)
Problem: cumulative_test Test of cumulative (defined in globals.  This version don't use temporary varibles which makes it (much) faster for some solvers. [OR] (2)
Problem: facility_location_problem Facility location problem [OR] (3)
Problem: factorial Factorial (alternative version not using the prod predicate) [Misc] (2)
Problem: fairies (2)
Problem: fair_split_into_3_groups (2)
Problem: fair_xmas_duty_2014 Fair Xmas duty 2014 (Swedish holidays) [Puzzle] (2)
Problem: family_riddle Family riddle [Puzzle] (2)
Problem: family_riddle2 Family riddle (variant) [Puzzle] (2)
Problem: fancy Mr Greenguest puzzle (Fancy dress puzzle) [Puzzle] (12)
Problem: farmer_and_cows Farmer and cows problem [Puzzle] (2)
Problem: farm_puzzle Farm puzzle, more general model [Puzzle] (2)
Problem: fib (5)
Problem: fill_a_pix Fill-a-pix puzzle.
[Puzzle] (18)
Problem: filling_table_with_ticks (2)
Problem: fill_in_the_squares Fill in the squares (Brainjammer problem) [Puzzle] (7)
Problem: final_student Final Student problem (Chris Smith)
[Puzzle] (3)
Problem: finding_celebrities Finding celebrities at a party (indicence matrix). [Combinatorial] (8)
Problem: finding_celebrities2 Finding celebrities at a party, using only set constraints. [Combinatorial] (3)
Problem: five (alternative model: (3)
Problem: five_brigands (7)
Problem: five_elements Five elements problem (Charles W. Trigg) [Puzzle] (3)
Problem: five_floors Five floors problem (Dinesman) [Puzzle] (6)
Problem: five_statements Five statements problem (logic problem) [Puzzle] (3)
Problem: five_translators Five translators (set version) [Puzzle] (2)
Problem: five_translators2 Five translators, matrix 0/1 version [Puzzle] (2)
Problem: fixed_charge Fixed charged problem (OPL) [OR] (4)
Problem: fix_points Number of fix points in an array [Combinatorial] (2)
Problem: fizzbuzz Fizz buzz problem [Misc] (2)
Problem: football Buying soccer players (lp_solve mailing list) [OR] (4)
Problem: four_islands Four islands puzzle (Dell Logic Puzzles) [Puzzle] (13)
Problem: four_numbers (2)
Problem: four_rectangles Four rectangles puzzle (Mind Your Decisions problem) [Puzzle] (2)
Problem: four_same_friends Four same friends problem [Puzzle] (2)
Problem: four_trees Four trees problem (Logic4Fun) [Puzzle] (2)
Problem: fractions Fractions, alphametic problem (standard Prolog benchmark) [Puzzle] (7)
Problem: franklin_8x8_magic_square Benjamin Franklin's 8x8 Magic Square [Puzzle] (2)
Problem: freight_transfer Freight Transfer (John Hooker) [OR] (2)
Problem: friends_at_different_floors (2)
Problem: frog_circle (2)
Problem: frustration_patience (2)
Problem: full_adder Full adder (digital circuit) [Misc] (2)
Problem: funny_dice Funny dice problem (Sunday Times teaser 2739) [Puzzle] (2)
Problem: furniture Furniture problem (best combination of offers to buy furnitures) [OR] (2)
Problem: furnituremovingtransition Optimizing furniture moving (Marriott and Stuckey) [OR] (22)
Problem: furniture_moving2 (2)
Problem: futoshiki Futoshiki puzzle [Puzzle] (18)
Problem: g4g_matrix Bernardo Recamán's 10x10 matrix puzzle (from CelebrationOfMind Google Hangout 20131021) [Martin Gardner] (2)
Problem: games Simple game theory example (Vanderbei "Linear Programming - Foundations - and Extensions", page 147ff) [Nonlinear/Var float] (3)
Problem: game_theory_taha Game theory, zero sum game (Taha, Operations Research) [Nonlinear/Var float] (8)
Problem: gap Generalized Assignment Problem (GLPK, AMPL) [OR] (2)
Problem: gardner_dinner Dinner problem [Martin Gardner] (2)
Problem: gardner_prime_puzzle Martin Gardner's prime puzzle [Martin Gardner] (2)
Problem: gardner_sum_square Martin Gardner's Sum Square problem (from Scampi) [Martin Gardner] (2)
Problem: gardner_two_plus_two TWO+TWO=FOUR problem [Martin Gardner] (2)
Problem: gather_homage_martin GATHER+HOMAGE=MARTIN (from CelebrationOfMind Google Hangout 20131021) [Martin Gardner] (2)
Problem: gcd_lcm Decomposition of gcd(a,b,GCD)
and lcm(a,b,LCM)
(not very efficient if all variables are decision variables) [Global constraint] (2)
Problem: generalized_knapsack_problem Generalized knapsack problem [Combinatorial] (2)
Problem: general_store General store problem (Sam Loyd) [Puzzle] (10)
Problem: generating_numbers_sat (2)
Problem: generating_numbers2 (2)
Problem: giant_cat_army_riddle Giant Cat Army riddle [Puzzle] (4)
Problem: giapetto Simple optimization problem of maximizing profit [OR] (3)
Problem: global_cardinality (4)
Problem: global_cardinality_no_loop global_cardinality_no_loop [Global constraint] (2)
Problem: global_cardinality_table global_cardinality, using a table with the occurrences [Global constraint] (2)
Problem: global_cardinality_with_costs global_cardinality_with_costs [Global constraint] (2)
Problem: global_contiguity global_contiguity [Global constraint] (10)
Problem: global_contiguity2 global_contiguity (different approach) [Global constraint] (2)
Problem: global_contiguity_regular (3)
Problem: goal_programming1 (3)
Problem: golf_puzzle Golf puzzle (Sam Loyd) [Puzzle] (2)
Problem: golomb_ruler (10)
Problem: good_burger_puzzlor Good Burger (PuzzlOR) [Puzzle] (2)
Problem: graceful_labeling Graceful labeling problem [Combinatorial] (2)
Problem: graph_degree_sequence Degree sequence for graphs, both matrix and edge representation [Combinatorial] (2)
Problem: graph_partition Graph partitioning (example from Pascal Van Hentenryck, Laurent Michel: "Constraint-based local search", page 6f) [Combinatorial] (2)
Problem: gray_code Gray code [Combinatorial] (2)
Problem: greatest_combination (2)
Problem: greatest_subsequential_sum (2)
Problem: grid17x17 (2)
Problem: grid_puzzle (2)
Problem: grime_puzzle (2)
Problem: grocery (10)
Problem: guards_and_apples Guards and apple problem [Puzzle] (2)
Problem: hamming_distance Hamming distance [Combinatorial] (11)
Problem: handshaking (5)
Problem: hanging_weights Hanging weights puzzle [Puzzle] (7)
Problem: hardy_1729 Hardy's 1729 problem [Puzzle] (2)
Problem: harry_potter_seven_potions Harry Potter's seven potions problem [Puzzle] (2)
Problem: heterosquare Heterosquare problem [Puzzle] (10)
Problem: hidato Hidato puzzle [Puzzle] (19)
Problem: hidato_table Hidato puzzle, using a table
constraint. [Puzzle] (6)
Problem: high_iq_problem "High IQ problem" [Puzzle] (2)
Problem: hitchcock_transporation_problem Hitchcock-Koopmans transportation problem [OR] (2)
Problem: hitting_set Hitting set [Combinatorial] (2)
Problem: home_improvement Home improvement (from PuzzlOR) [OR] (2)
Problem: honey_division Honey division puzzle [Martin Chlond IP] (3)
Problem: houses (from Algebra 1, Glencoe/McGraw-Hill, 1998 via kanren) [Puzzle] (2)
Problem: how_many_passengers_are_in_carriage_9 (2)
Problem: how_old_am_i How old am I (from Choco) [Puzzle] (2)
Problem: huey_dewey_louie Huey, Dewey, Louie, logical problem from Marriott & Stuckey "Programming in Constraints" [Puzzle] (11)
Problem: hundred_fowls Hundred Fowls puzzle [Puzzle] (2)
Problem: ice_cream Ice cream production given monthly demand. [OR] (2)
Problem: imply imply [Global constraint] (2)
Problem: increasing_except_0 increasing_except_0 [Global constraint] (2)
Problem: indexed_sum indexed_sum [Global constraint] (2)
Problem: inflexions inflexions, number of peaks in a sequence [Global constraint] (2)
Problem: in_interval in_interval [Global constraint] (2)
Problem: initials_queue_problem (2)
Problem: in_relation in_relation [Global constraint] (2)
Problem: in_same_partition in_same_partition [Global constraint] (2)
Problem: in_set in_set (cf the built in "in") [Global constraint] (2)
Problem: integer_programming1 Simple integer programming problem [OR] (2)
Problem: inter_distance inter-distance (from Quimper) [Global constraint] (2)
Problem: int_value_precede int_value_precede [Global constraint] (2)
Problem: inverse (8)
Problem: inverse_within_range inverse within range [Global constraint] (2)
Problem: investment_problem Investment problem (constraint programming version) [OR] (2)
Problem: investment_problem_mip Investment problem (MIP version) [OR] (2)
Problem: isbn Some explorations in ISBN-13 [Misc] (12)
Problem: is_prime Check for primality [Misc] (2)
Problem: itemset_mining Itemset mining (both Closed and Maximal Frequent Itemset Mining) [Combinatorial] (2)
Problem: ith_pos_different_from_0 ith pos different from 0 [Global constraint] (2)
Problem: its_a_tie "It's a tie" problem (Dell Logic Puzzles) [Puzzle] (2)
Problem: jellybeans Jellybeans [Puzzle] (2)
Problem: jive_turkeys Jive turkeys [Martin Chlond IP] (3)
Problem: jobs (2)
- Answer Set Programming (Clingo v3): jobs.lp
- Answer Set Programming, Clingo v3): jobs.lp4
Problem: jobshop Job-Shop Scheduling Problem, general approach. [OR] (2)
Problem: jobs_puzzle Jobs puzzle (an automated reasoning problem, TPTP #19) [Puzzle] (12)
Problem: joshua Joshua and his rats [Martin Chlond IP] (3)
Problem: jssp Job-Shop Scheduling Problem (GLPK) (this is the MT06 problem instance) [OR] (2)
Problem: just_forgotten Just forgotten puzzle (Enigma 1517) [Puzzle] (19)
Problem: k4p2_graceful_graph K4P2 Graceful Graph [Combinatorial] (3)
Problem: k4p2gracefulgraph2 K4P2 Graceful Graph (more general model) [Combinatorial] (8)
Problem: kakuro Kakuro puzzle [Puzzle] (19)
Problem: kakuro2 Kakuro puzzle, alternative representation of the hints. [Puzzle] (4)
Problem: k_alldifferent k alldifferent (all rows satisfy the alldifferent constraint) [Global constraint] (2)
Problem: kaprekars_constant Kaprekar's Constant [Puzzle] (2)
Problem: kaprekars_constant2 Kaprekar's Constant (calculate the fixpoint for different lengths) [Puzzle] (2)
Problem: kenken2 KenKen puzzle [Puzzle] (17)
Problem: kidney_exchange Simple kidney exchange model (inspired by Pascal Van Hentenryck's introduction to the Coursera Course "Discrete Optimization") [Combinatorial] (2)
Problem: killer_sudoku Killer Sudoku puzzle [Puzzle] (20)
Problem: killer_sudoku2 Killer Sudoku puzzle, alternative representation of the hints [Puzzle] (2)
Problem: kiselman_semigroup_problem Kiselman's Semigroup problem. [Combinatorial] (2)
Problem: knapsack (8)
Problem: knapsack2 Another knapsack problem [Combinatorial] (2)
Problem: knapsack_investments Knapsack (investment) problem (Lundgren, Rönnqvist, Värbrand: Optimeringslära) [OR] (9)
Problem: knapsack_problem Knapsack problem [Combinatorial] (2)
Problem: knapsack_rosetta_code_01 Knapsack problem, 0/1 (Rosetta code) [Combinatorial] (5)
Problem: knapsack_rosetta_code_bounded Knapsack problem, bounded (Rosetta code) [Combinatorial] (5)
Problem: knapsack_rosetta_code_unbounded Knapsack problem (float), Unbounded (Rosetta code) [Combinatorial] (4)
Problem: knapsack_rosetta_code_unbounded_int Knapsack problem Unbounded, integer version of (3)
Problem: knights_path (4)
Problem: knight_tour_circuit (2)
Problem: kntdom Knight domination puzzle - all squares threatened [Martin Chlond IP] (3)
Problem: kordemskys_palindrome_problem Kordemsky's Palindrome problem [Puzzle] (2)
Problem: kqueens Kraitchik's queen placement problem [Martin Chlond IP] (3)
Problem: kraftwerk_ticket_problem Kraftwerk ticket problem [OR] (2)
Problem: krypto Krypto puzzle (combine given numbers to an objective using the four basic arithmetic operations) [Puzzle] (2)
Problem: k_same k_same [Global constraint] (2)
Problem: k_same_modulo k_same_modulo [Global constraint] (2)
Problem: labeled_dice (20)
Problem: labeled_dice2 (2)
Problem: lager Stock model (Swedish) [OR] (2)
Problem: lams_problem Lam's problem (CSPLib problem 25) [Combinatorial] (2)
Problem: langford (20)
Problem: langford2 Langford's number problem (k=2) (CSPLib problem 24) [Combinatorial] (3)
Problem: langford_generalized Langford's number problem, (k >= 2) (CSPLib problem 24) [Combinatorial] (2)
Problem: language_round_table (2)
Problem: laplace Laplace problem (from CLP(R)) [Nonlinear/Var float] (2)
Problem: latin_square_card_puzzle Latin square card puzzle [Puzzle] (5)
Problem: latin_squares (5)
Problem: latin_squares_diagonals (3)
Problem: lccoin Lewis Carroll coin puzzle [Martin Chlond IP] (3)
Problem: leap_year Leap year [Misc] (2)
Problem: leastdiff2 Least diff problem: What is the smallest difference between two numbers X - Y if you must use all the digits (0..9) exactly once? [Puzzle] (25)
Problem: leastdiff2 (6)
Problem: least_square (3)
Problem: least_square_optimeringslara_286 Least sqauare (Lundgren, Rönnqvist, Värbrand: Optimeringslära) [OR] (2)
Problem: lectures Lectures, schedule problem from Biggs "Discrete Mathematics" [Combinatorial] (15)
Problem: lecture_series Lecture series puzzle (Dell Logic Puzzles) [Puzzle] (10)
Problem: lehmer_code_from_permutation Lehmer code from permutation [Combinatorial] (2)
Problem: letter_square Letter square problem (Vaderlind).
Data files: [Puzzle] (2)
Problem: lex_alldifferent lex_alldifferent [Global constraint] (2)
Problem: lex_between lex_between [Global constraint] (2)
Problem: lex_chain_less lex_chain_less [Global constraint] (2)
Problem: lex_different lex_different [Global constraint] (2)
Problem: library_books Library books (Logic4Fun) [Puzzle] (2)
Problem: lichtenstein_coloring Coloring problem: Lichtenstein's communes and exclaves [Combinatorial] (7)
Problem: life The Game of Life [Misc] (2)
Problem: light_meal Lightmeal problem (Colmerauer) [OR] (3)
Problem: lights Lights on puzzle [Martin Chlond IP] (3)
Problem: lights_out Lights out puzzle [Puzzle] (2)
Problem: lights_out_all Variant of Lights out puzzle (flip all cells in row and column) [Puzzle] (2)
Problem: limerick_primes Limerick Primes (see John D. [Puzzle] (2)
Problem: linear_combinations (3)
Problem: loading_pair_of_dice Loading a pair of dice (by cheating) [Puzzle] (2)
Problem: local_art_theft Local Art Theft problem. [Puzzle] (2)
Problem: locker Locker puzzle. [Puzzle] (2)
Problem: logical_design Logical design (Williams) [Combinatorial] (2)
Problem: logic_puzzle_aop Logic puzzle (from The Art of Prolog) [Puzzle] (2)
Problem: longest_change longest change, size of the longest sub sequence which satisfy a comparison operator (such as !=, <, > etc) [Global constraint] (2)
Problem: longest_subset_of_five_positions Longest subset of five positions [Puzzle] (2)
Problem: lost_at_sea Lost at Sea (PuzzlOR) [Puzzle] (2)
Problem: lucky_number (2)
Problem: m12 (2)
Problem: magic Magic square, integer programming (GLPK) [Puzzle] (2)
Problem: magic_hexagon (8)
Problem: magic_modulo_number Magic modulo number (from Scampi) [Puzzle] (2)
Problem: magic_sequence Magic sequence (CSPLib) [Puzzle] (14)
Problem: magic_series Magic series [Puzzle] (2)
Problem: magic_square Magic squares [Puzzle] (18)
Problem: magic_square2 (2)
Problem: magic_square_and_cards (11)
Problem: magic_square_associate Associative Magic squares [Puzzle] (2)
Problem: magic_square_frenicle_form (2)
Problem: magic_square_mip (3)
Problem: magic_square_primes Magic squares with only prime numbers [Puzzle] (2)
Problem: magic_squares_and_cards Magic squares and cards [Martin Gardner] (3)
Problem: magic_square_water_retention Magic squares water retention problem [Puzzle] (4)
Problem: make_a_good_burger Make a Good Burger problem [OR] (2)
Problem: mamas_age Mama's age (Dudeney) [Puzzle] (8)
Problem: manasa_and_stones Manasa and Stones problem [Puzzle] (2)
Problem: mango_puzzle Mango puzzle [Martin Chlond IP] (3)
Problem: mankell (5)
Problem: map Simple coloring of a map [Combinatorial] (16)
Problem: map2 Simple coloring of a map (using symmetry breaking with precedence/1) [Combinatorial] (7)
Problem: map_coloring (10)
Problem: map_coloring2 (2)
Problem: map_coloring_with_costs Map coloring (of South America) where each color has a cost [Combinatorial] (2)
Problem: marathon Marathon puzzle (XPress example), MIP model [Puzzle] (5)
Problem: marathon2 Marathon puzzle (XPress example), CP model [Puzzle] (17)
Problem: markov_chains Markov chain of market shares (from "Statistisk Dataanalys") [Nonlinear/Var float] (2)
Problem: markov_chains_taha Markov chains (fertlizer example from Taha "Operations Research") [Nonlinear/Var float] (3)
Problem: matchmaker Matchmaker problem (from PuzzlOr) [OR] (2)
Problem: matrix2num Converts a binary matrix to/frm a list of integers. [Misc] (2)
Problem: max_activity (2)
Problem: max_activity2 (2)
Problem: max_cut Maximum cut problem (GLPK) [OR] (2)
Problem: maxflow Maximum flow problem (GLPK) [OR] (2)
Problem: max_flow_taha Maximum flow problem (Taha) [OR] (9)
Problem: max_flow_winston1 Maximum flow problem (Winston) [OR] (13)
Problem: maximal_independent_sets Maximal independent sets (cf (2)
Problem: maximal_non_segment_sum Maximal subsegment sum [Combinatorial] (2)
Problem: maximal_non_segment_sum_regular Maximal subsegment sum (using regular
constraint) [Combinatorial] (2)
Problem: maximum_density_still_life Maximum density still life [Combinatorial] (2)
Problem: maximum_modulo maximum_modulo [Global constraint] (2)
Problem: maximum_subarray Maximum subarray (Rosetta code) [Combinatorial] (2)
Problem: max_index max_index, (also the extension max_index_val) [Global constraint] (2)
Problem: max_m_in_row Max m in row (ensure that there are max m consecutive values in an array) [Note: This is a simpler variant of stretch_path, see below.] [Global constraint] (2)
Problem: max_n max_n [Global constraint] (2)
Problem: max_number_of_occurrences Max number of occurrences (StackOverflow) [Puzzle] (2)
Problem: max_nvalue max_nvalue [Global constraint] (2)
Problem: max_size_set_of_consecutive_var max_size_set_of_consecutive_var [Global constraint] (2)
Problem: mceverywhere McEverywhere problem (PuzzlOR) [OR] (2)
Problem: message_sending Message sending puzzle (cf all_paths_graph. [Puzzle] (2)
Problem: mfasp Minimum Feedback Arc Set Problem (GLPK) [OR] (2)
Problem: mfvsp Minimum Feedback Vertex Set Problem (GLPK) [OR] (2)
Problem: minesweeper Minesweeper puzzle [Puzzle] (28)
Problem: minimum_except_0 minimum_except_0 [Global constraint] (3)
Problem: minimum_greater_than minimum_greater_than [Global constraint] (2)
Problem: minimum_modulo minimum_modulo [Global constraint] (2)
Problem: minimum_weight_alldifferent minimum_weight_alldifferent [Global constraint] (2)
Problem: min_index min_index, (also the extension min_index_val) [Global constraint] (2)
Problem: min_n min_n [Global constraint] (2)
Problem: min_nvalue min_nvalue [Global constraint] (2)
Problem: minsum Minsum problem [Combinatorial] (2)
Problem: mislabeled_boxes Mislabeled boxes (theorem proving problem, TPTP #12) [Puzzle] (2)
Problem: misp Maximum Independent Set Problem (GLPK) (cf (2)
Problem: missing_digit Missing digit probblem [Puzzle] (2)
Problem: miss_manners Miss Manners' seating problem (standard benchmark for rule engines). Data: [Puzzle] (5)
Problem: money_change Simple money change problem [Puzzle] (4)
Problem: monkey_coconuts The Monkey and Coconuts problem [Martin Gardner] (2)
Problem: monks_and_doors Eight monks and four doors [Puzzle] (11)
Problem: monorail Monorail puzzle (Grand Tour).
[Puzzle] (2)
Problem: mortgage Mortgage (standard constraint programming problem) [Nonlinear/Var float] (5)
Problem: movement_puzzle Movement puzzle (1d array) [Puzzle] (2)
Problem: movie_scheduling Movie scheduling (Steven Skiena) [Combinatorial] (2)
Problem: movie_stars Movie Stars (from PuzzlOR) [OR] (2)
Problem: moving_coins Moving coins in a triangle (generalized model) [Puzzle] (2)
Problem: m_queens_on_n_board M queens on a N x N board [Puzzle] (2)
Problem: mr_smith Mr Smith problem (IF Prolog) [Puzzle] (18)
Problem: muddle_management Muddle management (Logic4Fun) [Puzzle] (2)
Problem: multipl Unknown multiplication (standard Prolog benchmark) [Puzzle] (2)
Problem: multiplicative_sequence Multiplicative sequence [Puzzle] (2)
Problem: murder Murder puzzle [Puzzle] (2)
Problem: music_men Music men puzzle [Puzzle] (9)
Problem: mvcp Minimum Vertex Cover Problem (GLPK) [OR] (2)
Problem: nadel B.A. Nadel's construction problem [OR] (9)
Problem: narcissistic_numbers Narcissistic numbers [Puzzle] (2)
Problem: nchange n_change [Global constraint] (2)
Problem: nclass nclass [Global constraint] (2)
Problem: newspaper Scheduling newspapers reading (French '82, Duncan '90) [OR] (2)
Problem: next_element next_element [Global constraint] (2)
Problem: next_greater_element next_greater_element [Global constraint] (2)
Problem: nim (3)
Problem: nine_digit_arrangement Nine digit arrangement [Martin Gardner] (2)
Problem: nine_to_one_equals_100 Nine to one equals 100 [Martin Gardner] (2)
Problem: non_dominating_queens Non-dominating queens problem [Martin Chlond IP] (3)
Problem: nonlin2 Non linear problem (Taha) [Nonlinear/Var float] (3)
Problem: nonogram Nonogram, a. [Puzzle] (3)
Problem: nonogram_regular Nongoram, a.  [OR] (2)
Problem: ormat_game (8)
Problem: or_seating (2)
Problem: orth_link_ori_siz_end orth_link_ori_siz_end [Global constraint] (2)
Problem: orth_on_the_ground orth_on_the_ground [Global constraint] (2)
Problem: pair_divides_the_sum Pair divides the sum problem [Puzzle] (7)
Problem: pairwise_sum_of_n_numbers (2)
Problem: pandigital_numbers Pandigital numbers (any base <= 10) [Puzzle] (15)
Problem: parallel_resistors Parallel resistors problem problem from Marriott & Stuckey "Programming in Constraints" [Combinatorial] (2)
Problem: partial_latin_square Partial Latin squares [Combinatorial] (2)
Problem: partition (2)
Problem: partition_function (2)
Problem: partition_into_subset_of_equal_values (2)
Problem: partition_into_subsets_of_equal_values (5)
Problem: partition_into_subsets_of_equal_values2 (2)
Problem: party_mixing Party mixing (mixing people at different tables), (2)
Problem: path_from_to path_from_to, find a path from FROM to TO in a graph (incidence matrix) [Global constraint] (2)
Problem: patient_no_21 Patient No. 21 (From PuzzlOR) [OR] (2)
Problem: pchange Price change puzzle [Martin Chlond IP] (2)
Problem: peaceablearmyofqueens Peaceable Army of Queens [Puzzle] (2)
Problem: penguin Nonmonotonic reasoning: can Tweety - a penguin - fly? (Alma-0) [Misc] (2)
Problem: pentonomies (2)
Problem: perfect_shuffle Perfect shuffle [Combinatorial] (2)
Problem: perfect_square_sequence Perfect square sequence [Puzzle] (10)
Problem: period period (a sequence must have a period of a specific length) [Global constraint] (2)
Problem: permutation3 permutation3(a,p,b) and permutation3(a,b): ensure that array b is a permutation of array a (via a permutation p) [Global constraint] (2)
Problem: permutation_number Permutation number [Misc] (2)
Problem: permutation_symmetry Permutation symmetry [Puzzle] (3)
Problem: persistent_numbers Persistent numbers [Martin Gardner] (2)
Problem: pert PERT problem (van Hentenryck) [OR] (11)
Problem: philosophical_railway Philosophical railway [Puzzle] (2)
Problem: photo (2)
- Answer Set Programming (Clingo v3): photo.lp
- Answer Set Programming, Clingo v3): photo.lp4
Problem: photo_problem (16)
Problem: photo_stackoverflow Another photo problem [Puzzle] (2)
Problem: picking_teams Picking teams (where the objective is to minimize the differences in total strength of each team). [Combinatorial] (6)
Problem: picking_teams2 (2)
Problem: pigeon_hole Pigeon hole problem (CLP-FD) [Combinatorial] (11)
Problem: pilgrim The Riddle of the Pilgrims [Martin Chlond IP] (3)
Problem: place_number Placing Number Puzzle [Puzzle] (4)
Problem: place_number_puzzle (18)
Problem: plan Planning model (GLPK) [Nonlinear/Var float] (2)
Problem: planet_colonization_puzzlor Planet Colonization (PuzzlOR problem) [Puzzle] (2)
Problem: p_median P-median problem (OPL) [Nonlinear/Var float] (13)
Problem: polydivisible_numbers (2)
Problem: polygon Polygon (OPL) [Nonlinear/Var float] (2)
Problem: pool_ball_triangles Pool-ball triangles [Martin Gardner] (2)
Problem: popsicle_stand Popsicle stand problem (PuzzlOR) [OR] (2)
Problem: portfolio_optimization2 Portfolio optimization (from Xpress-Mosel) [Combinatorial] (2)
Problem: post_office_problem Post office problem (Winston) [OR] (5)
Problem: post_office_problem2 Post office problem, generalized model (Winston) [OR] (13)
Problem: power_set Power set [Combinatorial] (2)
Problem: prime_looking Prime-looking number (from Scampi/OscaR) [Martin Gardner] (2)
Problem: prime_multiplication Prime multiplication [Martin Gardner] (2)
Problem: prime_number (2)
Problem: primes_in_a_circle Primes in a circle [Puzzle] (2)
Problem: prod0 Optimization problem (AMPL) [Nonlinear/Var float] (2)
Problem: product_configuration Product configuration (John Hooker) [OR] (2)
Problem: product_ctr product_ctr [Global constraint] (2)
Problem: production (4)
Problem: public_school_problem Public School Problem [Martin Chlond IP] (3)
Problem: puzzle1 Yet another column/row sum problem [Puzzle] (3)
Problem: pyramid_of_numbers Pyramid of numbers (Rosetta code) [Puzzle] (2)
Problem: pythagoras Pythagoras number [Misc] (9)
Problem: quasigroup_completion Quasigroup completion problem [Combinatorial] (29)
Problem: queens (3)
Problem: queens4 n-queens problem, using alldifferent [Puzzle] (2)
Problem: queens_and_knights Queens and Knights [Puzzle] (2)
Problem: queens_diversity n-queens diversity problem [Puzzle] (3)
Problem: queens_ip n-queens problem, integer programming model (GLPK) [Puzzle] (2)
Problem: rabbits (9)
Problem: ramsey_partition Ramsey partition problem [Combinatorial] (2)
Problem: range_ctr range_ctr [Global constraint] (2)
Problem: raven_puzzle (2)
Problem: read_test (2)
Problem: rectangle_from_line_segments (2)
Problem: regex (2)
Problem: regexp (3)
Problem: regular (6)
Problem: rehearsal Rehearsal problem (Barbara M. Smith) [Combinatorial] (3)
Problem: reindeer_ordering Reindeer ordering (Decision Management Community problem) [Puzzle] (2)
Problem: relative_sizes Relative sizes puzzle (Enigma 1515) [Puzzle] (2)
Problem: relief_mission Relief mission (from PuzzlOR) [OR] (3)
Problem: remainder_puzzle (alternative model: (2)
Problem: remainder_puzzle2 (3)
Problem: remainders (7)
Problem: remarkable_sequence Remarkable sequence (from an Alma-0 model), i.e Langford problem n=9, k=3. [Puzzle] (7)
Problem: restaurant_scheduling Restaurant scheduling (PuzzlOR) [Combinatorial] (2)
Problem: reveal_the_mapping (2)
Problem: reverse_multiples Reverse multiples [Puzzle] (2)
Problem: rock_star_dressing_problem Rock star dressing problem [Puzzle] (2)
Problem: rogo Rogo grid puzzle, (2)
Problem: rogo2 (10)
Problem: rogo_20110106 (3)
Problem: rogo_20110107 (3)
Problem: rogo_mike_trick (3)
Problem: rook_path Rook path (on a square matrix) [Puzzle] (2)
Problem: rookwise_chain Rookwise Chain [Martin Gardner] (2)
Problem: rosenbrock Rosenbrock function [Nonlinear/Var float] (2)
Problem: rostering Rostering problem (Regin) [OR] (2)
Problem: rot13 Rot 13 (Caesar) cipher [Misc] (4)
Problem: rotating_discs Rotating discs (from Jean-Luis Lauriere's ALICE paper, page 84f) [Puzzle] (2)
Problem: rotation Nokia's "rotation puzzle" [Puzzle] (2)
Problem: rubiks_cube Rubik's cube, find the optimal number of moves. Using only the 6 permutations representing the moves, and their inverses. [Puzzle] (2)
Problem: runs Number of runs in an array (sequence) [Combinatorial] (3)
Problem: safe_cracking Safe cracking [Puzzle] (17)
Problem: same same [Global constraint] (2)
Problem: same_and_global_cardinality same_and_global_cardinality [Global constraint] (2)
Problem: same_and_global_cardinality_low_up same_and_global_cardinality_low_up [Global constraint] (2)
Problem: same_interval same_interval [Global constraint] (2)
Problem: same_modulo same_modulo [Global constraint] (2)
Problem: samurai_puzzle Samuraï grid puzzle [Puzzle] (2)
Problem: sangraal (2)
Problem: sat Satisfiability Problem, integer programming (GLPK) [Combinatorial] (4)
Problem: satisfy Satisfiability Problem (Alma-0) [Combinatorial] (2)
Problem: scanner_problem Scanner problem [Combinatorial] (2)
Problem: schedule1 Scheduling using cumulative constraint (Sicstus) [OR] (8)
Problem: schedule2 Scheduling problem, yet another (from Shasha "Puzzles for Programmers and Pros", page 131f) [OR] (5)
Problem: scheduling_speakers Scheduling speakers (Rina Dechter) [OR] (19)
Problem: scheduling_speakers_optimize (2)
Problem: scheduling_with_assignments Scheduling with assignments of the workers (and a lot of different outputs such as assignment matrices, schedules, and timelines for jobs as well as for the workers in a Gantt-like manner). It also supports precedences, enforcing non-idleness for the workers (flag allow_idle=false
, see #10, Graham's bicycle assembly problem), and also enforce that the tasks must be done by "nearby" workers (collect_workers=true
, see #14, perfect square placement). [OR] (2)
Problem: scheduling_with_multiple_workers Scheduling with parallel machines. [OR] (2)
Problem: schoolgirls (2)
Problem: scp41 Set covering problem (orlib #41) [Combinatorial] (2)
Problem: scrabble_contest (2)
Problem: seating_arrangements (2)
Problem: seating_plan Seating plan (Daniel L. Dudley, The Nut Cracker suit #1) [Puzzle] (2)
Problem: seating_row Seating placement, row (e. [Combinatorial] (2)
Problem: seating_table Seating placement, table (circular) [Combinatorial] (2)
Problem: secret_santa Secret Santa problem [Puzzle] (14)
Problem: secret_santa2 Another Secret Santa problem [Puzzle] (12)
Problem: self_referential_quiz Self-referential quiz [Puzzle] (2)
Problem: self_referential_sentence Self-referential sentence [Puzzle] (2)
Problem: send_more_money Alphametic puzzle: SEND + MORE = MONEY [Puzzle] (16)
Problem: send_more_money2 Alphametic puzzle: SEND + MORE = MONEY, alternative model [Puzzle] (7)
Problem: send_more_money_any_base Alphametic puzzle: SEND + MORE = MONEY, in any base [Puzzle] (21)
Problem: send_more_money_ip Alphametic puzzle: SEND + MORE = MONEY, integer programming model (GLPK) [Puzzle] (2)
Problem: send_more_money_scalar_product (2)
Problem: send_most_money Alphametic puzzle: SEND + MOST = MONEY (maximize MONEY) [Puzzle] (24)
Problem: send_most_money2 (2)
Problem: separate_zeros Copy an array but place all zeros (or some specific value) first (or last) [Global constraint] (2)
Problem: sequence (5)
Problem: sequence_2_3 Simple permutation puzzle [Puzzle] (2)
Problem: sequence_problem (2)
Problem: sequence_puzzle (2)
Problem: sequencesum (2)
Problem: serial_crack (2)
Problem: seseman (30)
Problem: seseman2 Seseman Convent problem, generalized model [Puzzle] (2)
Problem: set_covering Set covering, placing of firestations (Winston) [Combinatorial] (22)
Problem: set_covering2 Set covering, number of security telephons on a campus (Taha) [Combinatorial] (20)
Problem: set_covering3 Set covering, senators making a committe (Murty) [Combinatorial] (21)
Problem: set_covering3_b (2)
Problem: set_covering4 Set covering problem (Lundgren, Rönnqvist, Värbrand "Optimeringslära") [Combinatorial] (21)
Problem: set_covering5 Set covering, work scheduling (Lundgren, Rönnqvist, Värbrand "Optimeringslära") [Combinatorial] (5)
Problem: set_covering6 (3)
Problem: set_covering_b (2)
Problem: set_covering_deployment Set covering deployment [Combinatorial] (21)
Problem: set_covering_opl Set covering (OPL) [Combinatorial] (5)
Problem: set_covering_skiena Set covering (Skiena) [Combinatorial] (17)
Problem: set_packing Set packing [Combinatorial] (3)
Problem: set_partition Set partitioning [Combinatorial] (19)
Problem: set_partition_stackoverflow (2)
Problem: set_puzzle (2)
Problem: seven11
[Martin Chlond IP] (2)
Problem: shift shift [Global constraint] (2)
Problem: shopping_basket6 Optimize a shopping basket with delivery costs. [OR] (2)
Problem: shopping_with_delivery_costs Shopping with delivery costs. [OR] (2)
Problem: shortest_path1 Shortest path problem, selling/buying a car (Winston) [Combinatorial] (3)
Problem: shortest_path2 Shortest path problem (Winston) [Combinatorial] (3)
Problem: shortest_path_graph Shortest path problem (3 jugs problem as a graph, a bit experimental) [Combinatorial] (2)
Problem: sicherman_dice Sicherman dice problem [Combinatorial] (18)
Problem: sieve Another number theory stuff [Misc] (2)
Problem: ski_assignment (18)
Problem: ski_assignment_problem Ski assignment problem [OR] (2)
Problem: skyscraper Skyscraper puzzle [Puzzle] (4)
Problem: sliding_sum (9)
Problem: sliding_time_window sliding_time_window [Global constraint] (2)
Problem: sliding_time_window_from_start sliding_time_window_from_start [Global constraint] (2)
Problem: smallest_winning_electoral (2)
Problem: smooth smooth [Global constraint] (2)
Problem: smuggler_knapsack Smuggler's knapsack (Marriott and Stuckey: "Programming with Constraints") [Combinatorial] (4)
Problem: smugglers_knapsack (4)
Problem: smullyan_knights_knaves Raymond Smullyan's Knights and Knaves problems [Puzzle] (2)
Problem: smullyan_knights_knaves_normals Raymond Smullyan's Knights, Knaves, and Normals problems [Puzzle] (2)
Problem: smullyan_knights_knaves_normals_bahava Raymond Smullyan's Knights, Knaves, and Normals at the Island of Bahava problems [Puzzle] (2)
Problem: smullyan_lion_and_unicorn Raymond Smullyan's Lion and Unicorn problems [Puzzle] (2)
Problem: smullyan_portia Raymond Smullyan's Portia problems [Puzzle] (3)
Problem: soccer_puzzle Soccer puzzle [Puzzle] (2)
Problem: social_golfer1 (2)
Problem: social_golfers1 Social golfers (OPL) [OR] (4)
Problem: social_golfers2 (2)
Problem: soft_all_equal_ctr soft_all_equal_ctr [Global constraint] (2)
Problem: soft_same_var soft_same_var [Global constraint] (2)
Problem: sonet (3)
Problem: sonet_problem SONET problem [Combinatorial] (5)
Problem: sortedness (2)
Problem: sort_permutation sort_permutation [Global constraint] (2)
Problem: special_6_digit_number Special 6 digit number problem (Mind Your Decisions) [Puzzle] (2)
Problem: spinning_disks (2)
Problem: spp Shortest path problem, integer programming (GLPK) [OR] (2)
Problem: spreadsheet Simple spreadsheet problem [Nonlinear/Var float] (8)
Problem: spy_girls Spy girls problem [Puzzle] (2)
Problem: square_root_of_wonderful Square Root of Wonderful [Martin Gardner] (6)
Problem: squeens Schuh's queen placement problem [Martin Chlond IP] (3)
Problem: stable_marriage Stable marriage [OR] (17)
Problem: stable_marriage_random (2)
Problem: stamp_licking The gentle art of stamp-licking [Martin Chlond IP] (3)
Problem: state_name_puzzle (2)
Problem: steiner Steiner triplet problem [Combinatorial] (10)
Problem: stigler Original Stigler's 1939 diet problem (GLPK) [Nonlinear/Var float] (5)
Problem: stretch_path stretch_path [Global constraint] (2)
Problem: strimko (3)
Problem: strimko2 (18)
Problem: strimko2_002 (3)
Problem: strimko2_067 (3)
Problem: strimko2_068 (3)
Problem: strimko2_069 (3)
Problem: strimko2_070 (3)
Problem: stuckey_assignment Assignment problem (Marriott and Stuckey) [OR] (2)
Problem: stuckey_finite_element Finite element (Marriott, Stuckey: Programming in Constraint, 191ff) [Nonlinear/Var float] (2)
Problem: stuckey_seesaw Balancing on a seesaw (Marriot and Stuckey) [OR] (10)
Problem: subsequence subsequence [Global constraint] (2)
Problem: subsequence_sum subsequence sum [Global constraint] (2)
Problem: subsets_100 Subsets 100 (rec.puzzles FAQ) [Puzzle] (2)
Problem: subset_sum Subset sum (Murty) [Combinatorial] (21)
Problem: successive_number_problem (2)
Problem: sudoku (16)
Problem: sudoku_17_hints_sat (2)
Problem: sudoku2 (4)
Problem: sudoku_4x4 (2)
Problem: sudoku_gcc Sudoku, using the global cardinality constraint.
[Puzzle] (3)
Problem: sudoku_ip Sudoku, integer programming (GLPK) [Puzzle] (3)
Problem: sudoku_mip_sat (2)
Problem: sudoku_multi Multi-Sudoku (two connected Sudokus) [Puzzle] (2)
Problem: sudoku_problems (3)
Problem: sultans_children Sultan's children problem [Puzzle] (2)
Problem: sumbrero Sumbrero puzzle [Puzzle] (2)
Problem: sum_ctr sum ctr [Global constraint] (2)
Problem: sum_first_and_last (2)
Problem: sum_free sum free, also: product_free [Global constraint] (2)
Problem: sum_of_next_natural_numbers Sum of next (increasing) natural numbers [Misc] (2)
Problem: sum_of_weights_of_distinct_values sum_of_weights_of_distinct_values [Global constraint] (2)
Problem: sum_set sum set [Global constraint] (2)
Problem: sum_to_100 Five numbers should sum to 100, and all numbers must be divisible by 2 or 5 [Puzzle] (2)
Problem: super_number Super number puzzle (the first i digits of a 10 digit number is divisible by i) [Puzzle] (2)
Problem: superpermutations Superpermutation problem
Instances: [Combinatorial] (2)
Problem: survivor Survivor problem (from PuzzlOr) [OR] (2)
Problem: survo_puzzle Survo puzzle [Puzzle] (30)
Problem: symmetric symmetric [Global constraint] (2)
Problem: symmetric_alldifferent symmetric_alldifferent [Global constraint] (2)
Problem: symmetry_breaking Example of symmetry breaking for a math problem [Misc] (2)
Problem: table (3)
Problem: table_of_numbers (2)
Problem: takuzu Takuzu grid puzzle [Puzzle] (2)
Problem: talent Talent example (OPL) [OR] (2)
Problem: talisman_square Talisman Square [Puzzle] (10)
Problem: tank (2)
Problem: tantalizer_487_number_system Tantalizer 487: Number System [Puzzle] (2)
Problem: team_building Teambuilding (OPL) [OR] (2)
Problem: tea_mixing Dudeney's tea mixing problem [Martin Chlond IP] (3)
Problem: telephone_number (2)
Problem: temporal_reasoning Temporal reasoning (Apt) [Combinatorial] (4)
Problem: tennis_problem Tennis problem (Jean-Loius Laurière) [Puzzle] (2)
Problem: tennis_tournament Tennis tournament scheduling [Puzzle] (2)
Problem: ten_statements (2)
Problem: tents_puzzle Tents puzzle [Puzzle] (2)
Problem: the_birthday Birthday game theory problem [Nonlinear/Var float] (2)
Problem: the_bomb The bomb, logical puzzle (Janko "Die Bombe") [Puzzle] (2)
Problem: the_family_puzzle (6)
Problem: the_interns The Interns problem (theorem proving problem, TPTP #18) [Puzzle] (2)
Problem: thick_as_thieves Thick as thieves (Logic4Fun) [Puzzle] (2)
Problem: thirteen_link_chain_puzzle (2)
Problem: three_consecutive_numbers Three consecutive numbers (Mind Your Decisions problem) [Puzzle] (2)
Problem: three_digit Three digit problem [Puzzle] (2)
Problem: three_in_a_row_puzzle 3-in-a-row puzzle [Puzzle] (2)
Problem: tictactoe_avoidance (2)
Problem: timeslots_for_songs (2)
Problem: timetable Timetable of courses (from Alma-0) [OR] (2)
Problem: timpkin Mrs Timpkin's age problem (Dudeney) [Puzzle] (11)
Problem: tobacco Clarke's tobacconist [Martin Chlond IP] (3)
Problem: tomography Discrete Tomography (one color model) [Puzzle] (5)
Problem: tomography_n_colors Discrete Tomography (n color model) [Puzzle] (2)
Problem: to_num (21)
Problem: torn_number Torn number puzzle (Dudeney) [Puzzle] (3)
Problem: torn_numbers (6)
Problem: touching_numbers (2)
Problem: tourist_site_competition Tourist site competition (Pierre Flener) [Combinatorial] (12)
Problem: traffic_lights Traffic lights problem (CSPLib problem 16) [Combinatorial] (20)
Problem: trains (3)
Problem: transp Transportation problem (GLPK) [Nonlinear/Var float] (3)
Problem: transp1 Transportation problem (OPL) [Nonlinear/Var float] (3)
Problem: transportation Transportation problem (ECLiPSe) [OR] (3)
Problem: transshipment Transshipment problem (Winston) [OR] (3)
Problem: trial1 The First Trial [Martin Chlond IP] (3)
Problem: trial12 The Logical Labyrinth [Martin Chlond IP] (2)
Problem: trial12_variant (2)
Problem: trial2 The Second Trial [Martin Chlond IP] (3)
Problem: trial3 The Third Trial [Martin Chlond IP] (3)
Problem: trial4 The Fourth Trial [Martin Chlond IP] (3)
Problem: trial5 The Fifth Trial [Martin Chlond IP] (3)
Problem: trial6 The Sixth Trial [Martin Chlond IP] (3)
Problem: triangles Triangles problem [Puzzle] (2)
Problem: tricky_multiple_question Tricky multiple question [Puzzle] (2)
Problem: tsp Travelling Salesman Problem, integer programming (GLPK) [OR] (6)
Problem: tsp_circuit Travelling salesperson problem, using circuit predicate [Combinatorial] (4)
Problem: tsptw Travelling salesperson problem with time windows [Combinatorial] (2)
Problem: tunapalooza Tunapalooza puzzle (Dell Logic Puzzles) [Puzzle] (9)
Problem: twelve Twelve draughts puzzle [Martin Chlond IP] (3)
Problem: twelve_statements Twelve statements puzzle [Puzzle] (2)
Problem: twin twin [Global constraint] (2)
Problem: twin_letters Twin letters [Puzzle] (10)
Problem: two_circles Two Circles problem [Nonlinear/Var float] (3)
Problem: two_cube_calendar Two cube calendar [Martin Gardner] (2)
Problem: two_dimensional_channels Two-dimensional constrained channels (all interiour cells must have m 1 neighbours in a NxN 0/1 matrix) [Combinatorial] (2)
Problem: uniform_dice Uniform dice [Combinatorial] (2)
Problem: uniform_dice2 Uniform dice (Mind Your Decisions) [Combinatorial] (2)
Problem: unique_set_puzzle (2)
Problem: urban_planning (2)
Problem: uzbekian_puzzle Uzbekian puzzle [Puzzle] (2)
Problem: vingt_cinq_cinq_trente VINGT+ CINQ + CINQ = TRENTE [Martin Gardner] (2)
Problem: volsay Volsay problem (OPL) [Nonlinear/Var float] (7)
Problem: volsay1 (5)
Problem: volsay2 Volsay problem, with arrays (OPL) [Nonlinear/Var float] (11)
Problem: volsay3 Volsay problem, with components (OPL) [Nonlinear/Var float] (9)
Problem: voltage_divider Voltage divider problem problem from Marriott & Stuckey "Programming in Constraints" [Nonlinear/Var float] (3)
Problem: warehouse (7)
Problem: warehouse_location (3)
Problem: war_or_peace War or peace problem (Alma-0) [Puzzle] (3)
Problem: water (2)
Problem: water_buckets1 Water bucket problem (generalized) [Puzzle] (3)
Problem: wedding_optimal_chart (5)
Problem: were2 Werewolves II [Martin Chlond IP] (3)
Problem: were4 Werewolves IV [Martin Chlond IP] (3)
Problem: who_killed_agatha Who killed agatha? (The Dreadsbury Mansion Murder Mystery, a automated reasoning problem, TPTP #1) [Puzzle] (26)
Problem: who_killed_agatha2 (2)
Problem: who_killed_the_bosmer (2)
Problem: wijuko Wijuko grid puzzle [Puzzle] (2)
Problem: wine_cask_puzzle Wine cask puzzle [Martin Chlond IP] (3)
Problem: wiseman_problem_20131129 Problem from Richard Wiseman 20131129 [Puzzle] (2)
Problem: word_golf Word golf (word chain) [Puzzle] (2)
Problem: wordle (3)
Problem: wordle_dcg (2)
Problem: word_square Word square: square matrix cross words (fill the whole square with unique words). [Puzzle] (13)
Problem: word_square2 (3)
Problem: work_shift_problem Work shift scheduling problem (from SAS/OR 9.22 User's Guide) [OR] (2)
Problem: wwr alphametic problem: WRONG + WRONG = RIGHT [Puzzle] (2)
Problem: xkcd (28)
Problem: young_tableaux Young tableaux [Combinatorial] (23)
Problem: young_tableaux_stack_overflow (2)
Problem: zebra (14)
Problem: zebra_ip Zebra puzzle, integer programming model (GLPK) [Puzzle] (2)
Problem: zebra_slow (2)
Problem: zoo_buses_and_kids Zoo, buses, and kids (DM Community) [Puzzle] (2)
By Hakan Kjellerstrand<EMAIL_ADDRESS>Also see: