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technical-note

Scripting and framework integration in heuristic optimization environments

Published: 12 July 2014 Publication History

Abstract

Rapid prototyping and testing of new ideas has been a major argument for evolutionary computation frameworks. These frameworks facilitate the application of evolutionary computation and allow experimenting with new and modified algorithms and problems by building on existing, well tested code. However, one could argue, that despite the many frameworks of the metaheuristics community, software packages such as MATLAB, GNU Octave, Scilab, or RStudio are quite popular. These software packages however are associated more closely with numerical analysis rather than evolutionary computation. In contrast to typical evolutionary computation frameworks which provide standard implementations of algorithms and problems, these popular frameworks provide a direct programming environment for the user and several helpful functions and mathematical operations. The user does not need to use traditional development tools such as a compiler or linker, but can implement, execute, and visualize his ideas directly within the environment. HeuristicLab has become a popular environment for heuristic optimization over the years, but has not been recognized as a programming environment so far. In this article we will describe new scripting capabilities created in HeuristicLab and give information on technical details of the implementation. Additionally, we show how the programming interface can be used to integrate further metaheuristic optimization frameworks in HeuristicLab. Categories and Subject D.

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    cover image ACM Conferences
    GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
    July 2014
    1524 pages
    ISBN:9781450328814
    DOI:10.1145/2598394
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 12 July 2014

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    Author Tags

    1. evolutionary computation frameworks
    2. heuristiclab
    3. metaheuristic optimization frameworks
    4. scripting

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    GECCO '14
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    GECCO '14: Genetic and Evolutionary Computation Conference
    July 12 - 16, 2014
    BC, Vancouver, Canada

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    GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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