JBoss.orgCommunity Documentation

Chapter 1. Planner introduction

1.1. What is OptaPlanner?
1.2. What is a planning problem?
1.2.1. A planning problem is NP-complete
1.2.2. A planning problem has (hard and soft) constraints
1.2.3. A planning problem has a huge search space
1.3. Download and run the examples
1.3.1. Get the release zip and run the examples
1.3.2. Run the examples in an IDE (IntelliJ, Eclipse, NetBeans)
1.3.3. Use OptaPlanner with Maven, Gradle, Ivy, Buildr or ANT
1.3.4. Build OptaPlanner from source
1.4. Status of OptaPlanner
1.5. Compatibility
1.6. Questions, issues and blog

OptaPlanner is a lightweight, embeddable planning engine that optimizes planning problems. It solves use cases, such as:

  • Employee shift rostering: timetabling nurses, repairmen, ...

  • Agenda scheduling: scheduling meetings, appointments, maintenance jobs, advertisements, ...

  • Educational timetabling: scheduling lessons, courses, exams, conference presentations, ...

  • Vehicle routing: planning vehicles (trucks, trains, boats, airplanes, ...) with freight and/or people

  • Bin packing: filling containers, trucks, ships and storage warehouses, but also cloud computers nodes, ...

  • Job shop scheduling: planning car assembly lines, machine queue planning, workforce task planning, ...

  • Cutting stock: minimizing waste while cutting paper, steel, carpet, ...

  • Sport scheduling: planning football leagues, baseball leagues, ...

  • Financial optimization: investment portfolio optimization, risk spreading, ...

Every organization faces planning problems: provide products or services with a limited set of constrained resources (employees, assets, time and money). OptaPlanner optimizes such planning to do more business with less resources. This is known as Constraint Satisfaction Programming (which is part of the discipline Operations Research).

OptaPlanner helps normal JavaTM programmers solve constraint satisfaction problems efficiently. Under the hood, it combines optimization heuristics and metaheuristics with very efficient score calculation.

OptaPlanner is open source software, released under the Apache Software License 2.0. This license is very liberal and allows reuse for commercial purposes. Read the layman's explanation. OptaPlanner is 100% pure JavaTM, runs on any JVM and is available in the Maven Central Repository too.

All the use cases above are probably NP-complete. In layman's terms, this means:

  • It's easy to verify a given solution to a problem in reasonable time.

  • There is no silver bullet to find the optimal solution of a problem in reasonable time (*).

Note

(*) At least, none of the smartest computer scientists in the world have found such a silver bullet yet. But if they find one for 1 NP-complete problem, it will work for every NP-complete problem.

In fact, there's a $ 1,000,000 reward for anyone that proves if such a silver bullet actually exists or not.

The implication of this is pretty dire: solving your problem is probably harder than you anticipated, because the 2 common techniques won't suffice:

  • A brute force algorithm (even a smarter variant) will take too long.

  • A quick algorithm, for example in bin packing, putting in the largest items first, will return a solution that is usually far from optimal.

By using advanced optimization algorithms, Planner does find a good solution in reasonable time for such planning problems.

A planning problem has a number of solutions. There are several categories of solutions:

Counterintuitively, the number of possible solutions is huge (if calculated correctly), even with a small dataset. As you can see in the examples, most instances have a lot more possible solutions than the minimal number of atoms in the known universe (10^80). Because there is no silver bullet to find the optimal solution, any implementation is forced to evaluate at least a subset of all those possible solutions.

OptaPlanner supports several optimization algorithms to efficiently wade through that incredibly large number of possible solutions. Depending on the use case, some optimization algorithms perform better than others, but it's impossible to tell in advance. With Planner, it is easy to switch the optimization algorithm, by changing the solver configuration in a few lines of XML or code.

To try it now:

The Examples GUI application will open. Just pick an example:

Note

Planner itself has no GUI dependencies. It runs just as well on a server or a mobile JVM as it does on the desktop.

The OptaPlanner jars are also available in the central maven repository (and also in the JBoss maven repository).

If you use Maven, add a dependency to optaplanner-core in your project's pom.xml:


    <dependency>
      <groupId>org.optaplanner</groupId>
      <artifactId>optaplanner-core</artifactId>
    </dependency>

This is similar for Gradle, Ivy and Buildr. To identify the latest version, check the central maven repository.

Because you might end up using other optaplanner modules too, it's recommended to import the optaplanner-bom in Maven's dependencyManagement so the optaplanner version is specified only once:


  <dependencyManagement>
    <dependencies>
      <dependency>
        <groupId>org.optaplanner</groupId>
        <artifactId>optaplanner-bom</artifactId>
        <type>pom</type>
        <version>...</version>
        <scope>import</scope>
      </dependency>
      ...
    </dependencies>
  </dependencyManagement>

If you're still using ANT (without Ivy), copy all the jars from the download zip's binaries directory and manually verify that your classpath doesn't contain duplicate jars.

Note

The download zip's binaries directory contains far more jars then optaplanner-core actually uses. It also contains the jars used by other modules, such as optaplanner-benchmark.

Check the maven repository pom.xml files to determine the minimal dependency set for a specific version of a specific module.

You can also easily build OptaPlanner from source yourself.

Set up Git and clone optaplanner from GitHub (or alternatively, download the zipball):

$ git clone git@github.com:droolsjbpm/optaplanner.git optaplanner
...

Then do a Maven 3 build:

$ cd optaplanner
$ mvn clean install -DskipTests
...

After that, you can run any example directly from the command line, just run this command and pick an example:

$ cd optaplanner-examples
$ mvn exec:exec
...

OptaPlanner is production ready. The API is almost stable but backward incompatible changes can occur. With the recipe called UpgradeFromPreviousVersionRecipe.txt you can easily upgrade to a newer version and quickly deal with any backwards incompatible changes. That recipe file is included in every release.

OptaPlanner is 100% pure JavaTM and runs on any JVM 1.6 or higher.

Your questions and comments are welcome on the user mailing list. Start the subject of your mail with [planner]. You can read/write to the user mailing list without littering your mailbox through this web forum or this newsgroup.

Feel free to report an issue (such as a bug, improvement or a new feature request) for the OptaPlanner code or for this manual to our issue tracker.

Pull requests are very welcome and get priority treatment! By open sourcing your improvements, you 'll benefit from our peer review and from our improvements made upon your improvements.

Check our blog, Google+ (OptaPlanner, Geoffrey De Smet) and twitter (Geoffrey De Smet) for news and articles. If OptaPlanner helps you solve your problem, don't forget to blog or tweet about it!