https://github.com/joelparkerhenderson/demo-optaplanner
Demo OptaPlanner constraint solver
https://github.com/joelparkerhenderson/demo-optaplanner
Last synced: 5 months ago
JSON representation
Demo OptaPlanner constraint solver
- Host: GitHub
- URL: https://github.com/joelparkerhenderson/demo-optaplanner
- Owner: joelparkerhenderson
- Created: 2019-10-31T04:01:49.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2023-06-15T06:41:25.000Z (over 2 years ago)
- Last Synced: 2025-05-07T05:08:53.673Z (5 months ago)
- Language: Java
- Size: 257 KB
- Stars: 6
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
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README
# Demo OptaPlanner
* [Introduction](#introduction)
* [Documentation](#documentation)
* [Technology](#technology)
* [Example](#example)
* [Initialization](#initialization)
* [Running](#running)
* [Run](#run)
* [Output](#output)
## Introduction
This is a demonstration of OptaPlanner, which is a constraint satisfaction solver tool.
When the demo app runs, it creates a demo constraint satisfaction problem, then solves it.
The constraint satisfaction problem is how to match makers (a.k.a. producers) with takers (a.k.a. consumers).
## Documentation
Documentation within this repo:
* [Documentation](doc/)
* [Setup](doc/setup.md)
* [Wordbooks](doc/wordbooks/README.md)
* [Plans](doc/plans/)
* [Roadmap](doc/plans/roadmap/)
* [Bootstrapping - WIP](doc/plans/bootstrapping.md)
* [Objects UML diagram - WIP](doc/plans/objects.png)
* [Integration with XML - WIP](doc/integration/xml.md)
* [Integration with JSON - TODO](doc/integration/json.md)
## Technology
The software implementation uses:
* [Java](https://www.java.com) programming language
* [OptaPlanner](https://www.optaplanner.org) open source contraint satisfaction solver
* [XStream](https://x-stream.github.io/) XML serializer/deserializer
* [SLF4J](http://www.slf4j.org/) (Simple Logging Facade for Java) for log messages.
* [Google Guava](https://github.com/google/guava) core libraries for Java, such as for collections.
* [Apache Commons](https://commons.apache.org/) for [Lang](https://commons.apache.org/proper/commons-lang/) and [Math].
## Example
When the app runs, it creates a demo constraint satisfaction problem, then solves it.
The constraint satisfaction problem is how to match makers (a.k.a. producers) with takers (a.k.a. consumers).
### Initialization
Initialization of facts:
* Create 10 makers. These are named 0 to 9.
* Create 10 takers. These are named 0 to 9.
Initialization of planning entities:
* Create 10 matchers. Each matcher can associate a maker and taker.
* Each matcher is loaded with a corresponding maker, because this represents the facts i.e. we want to match all the makers.
* Each matcher has null for the taker, because this is the planning variable i.e. we want to try to match on various takers.
### Running
Scorer pseudocode:
* Score each matcher by comparing its maker and taker.
* When the maker name and taker name are equal, then score +1 soft, else score -1 soft.
* The scorer will maximize matchers that associate a maker and taker with the same name.
Solution pseudocode:
* Create an OptaPlanner solver, and load it with the makers, takers, matchers, etc.
* Create a timeout of 1 minute. This is fine for the demo small scale.
* The solver will try associating the matchers with various takers, then report results.
See [setup.md](doc/setup.md)
### Output
The output shows the solution successfully associates all makers and takers.
The score `0hard` means the hard constraint score is 0, which is correct because the scorer had no hard contraints.
The score `10soft` means the soft constraint score is 10, which is correct because the solver matched all 10 makers and takers.
Output with log level info:
```sh
Demo OptaPlanner version 1.0.0
Initialize...
name:Demo Solution,
score:(0hard/0soft),
matchers:[
matcher:{name:0,maker:{name:0},taker:{null}},
matcher:{name:1,maker:{name:1},taker:{null}},
matcher:{name:2,maker:{name:2},taker:{null}},
matcher:{name:3,maker:{name:3},taker:{null}},
matcher:{name:4,maker:{name:4},taker:{null}},
matcher:{name:5,maker:{name:5},taker:{null}},
matcher:{name:6,maker:{name:6},taker:{null}},
matcher:{name:7,maker:{name:7},taker:{null}},
matcher:{name:8,maker:{name:8},taker:{null}},
matcher:{name:9,maker:{name:9},taker:{null}}]
Solved...
name:Demo Solution,
score:(0hard/10soft),
matchers:[
matcher:{name:0,maker:{name:0},taker:{name:0}},
matcher:{name:1,maker:{name:1},taker:{name:1}},
matcher:{name:2,maker:{name:2},taker:{name:2}},
matcher:{name:3,maker:{name:3},taker:{name:3}},
matcher:{name:4,maker:{name:4},taker:{name:4}},
matcher:{name:5,maker:{name:5},taker:{name:5}},
matcher:{name:6,maker:{name:6},taker:{name:6}},
matcher:{name:7,maker:{name:7},taker:{name:7}},
matcher:{name:8,maker:{name:8},taker:{name:8}},
matcher:{name:9,maker:{name:9},taker:{name:9}}]
```