HeuristicLab 3.3: A unified approach to metaheuristic optimization

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

The awareness of heuristic methods as optimization tools and their, in comparison to exact algorithms, quick and simple application has expanded to many different domains in the recent history. In the course of these developments the user base of heuristic optimization methods has also grown from mathematicians and computer scientists to practitioners in virtually every field. To facilitate the application of heuristic optimizers in domains where no computer-scientist has gone before, a number of more or less advanced software frameworks exists. In this paper the authors introduce a new version of their software environment HeuristicLab which aims to provide a comprehensive solution for algorithm development, testing, analysis and generally the optimization of complex problems.
OriginalspracheEnglisch
TitelActas del séptimo congreso español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB'2010)
Seitenumfang8
PublikationsstatusVeröffentlicht - 2010
VeranstaltungVII Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB'2010) - Valencia, Spain, Spanien
Dauer: 7 Sep 201010 Sep 2010

Konferenz

KonferenzVII Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB'2010)
LandSpanien
OrtValencia, Spain
Zeitraum07.09.201010.09.2010

Schlagwörter

  • evolutionary algorithms
  • optimization
  • software frameworks

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