Simplifying problem definitions in the HeuristicLab optimization environment

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2 Citations (Scopus)

Abstract

Software frameworks for metaheuristic optimization take the burden off researchers and practitioners to start from scratch and implement their own algorithms and problems. One such framework is HeuristicLab. While it allows using existing, already implemented algorithms and problems comfortably and provides an extensive range of tools for analyzing results, it lacks an easy to use programming interface for adding new problems. As implementing new problems is a common task, an improved and simpler problem definition interface has been created. Besides giving an overview of the implementation, we also show examples of problems built using this new interface. Additionally, we compare the new approach to three other metaheuristic frameworks. This is done by analyzing the source code of the OneMax problem implemented in each framework and comparing the resulting lines of code with previous works.

Original languageEnglish
Title of host publicationGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
EditorsSara Silva
PublisherAssociation for Computing Machinery, Inc
Pages1101-1108
Number of pages8
ISBN (Electronic)9781450334884
ISBN (Print)978-1-4503-3488-4
DOIs
Publication statusPublished - 11 Jul 2015
Event17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain
Duration: 11 Jul 201515 Jul 2015

Publication series

NameGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference

Conference

Conference17th Genetic and Evolutionary Computation Conference, GECCO 2015
CountrySpain
CityMadrid
Period11.07.201515.07.2015

Keywords

  • Evolutionary computation frameworks
  • HeuristicLab
  • Meta-heuristic optimization frameworks
  • Scripting

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