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wiki:AddonsDailyBuilds

Version 10 (modified by epitzer, 12 years ago) (diff)

add description of FLA plug-ins

HeuristicLab Branches Daily Builds

Besides daily builds of the trunk we also provide daily builds of some branches. Branches contain additional features for HeuristicLab which haven't yet been integrated in the trunk and are often under heavy development. Though these features haven't yet reached maturity, they may be useful for some people. Please note that branches are always developed against the trunk, so you need to either compile the trunk version of HeuristicLab by yourself or download the latest daily build from this location.

Below is a list of branches for which we provide daily builds as well as the links to the download location. The file, which you get when you click on the download link, is a zip file containing additional plugins. Extract these files in your HeuristicLab folder and restart HeuristicLab. The plugins will be automatically discovered and the new functionality can then be used.

Vehicle Routing Problem (VRP)

The vehicle routing problem (VRP) is a class of problems that frequently occurs in the field of transportation logistics. In plugin version 3.4, the implementation in HeuristicLab covers the capacitated problem formulation with time windows (CVRPTW), pickup and delivery formulations (PDPTW) and multiple depots (MDCVRPTW). Additional information and benchmark instances can be found at the Vehicle Routing Problem page?.

Job-Shop Scheduling Problem (JSSP)

Meta-Optimization and parameter grid tests

The meta-optimization plugin adds the meta-optimization problem to HeuristicLab. This problem allows to use heuristic optimization algorithms to find optimal parameter settings for heuristic optimization algorithms. It's also possible to let HeuristicLab automatically create experiments to test large ranges of parameters (parameter grid tests).

Fitness Landscape Analysis

The fitness landscape analysis plug-ins contain a set of algorithms and analyzers that can be used together or independently to explore the fitness landscape of arbitrary problems. Additionally, the a memory efficient implementation of large NK landscapes and support for several vehicle routing mutation operators are included.

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