tutorial

Algorithm and experiment design with heuristic lab: an open source optimization environment for research and education

Authors:

Stefan Wagner,

Gabriel KronbergerAuthors Info & Claims

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

Pages 1287 - 1316

https://doi.org/10.1145/2330784.2330941

Published: 07 July 2012 Publication History

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Abstract

This tutorial demonstrates how to apply and analyze metaheuristic optimization algorithms using the HeuristicLab open source optimization environment. It is shown how to parameterize and execute evolutionary algorithms to solve combinatorial optimization problems (traveling salesman, vehicle routing) as well as data analysis problems (regression, classification). The attendees learn how to assemble different algorithms and parameter settings to large scale optimization experiments and how to execute such experiments on multi-core or cluster systems. Furthermore, the experiment results are compared using HeuristicLab's interactive charts for visual and statistical analysis to gain knowledge from the executed test runs. To complete the tutorial, it is sketched briefly how HeuristicLab can be extended with further optimization problems and how custom optimization algorithms can be modeled using the graphical algorithm designer. Additional details on HeuristicLab can be found at http://dev.heuristiclab.com.

References

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S. Wagner, G. Kronberger, A. Beham, S. Winkler, M. Affenzeller Modeling of heuristic optimization algorithms Proceedings of the 20th European Modeling and Simulation Symposium, pp. 106-111 DIPTEM University of Genova, 2008.

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S. Wagner, G. Kronberger, A. Beham, S. Winkler, M. Affenzeller Model driven rapid prototyping of heuristic optimization algorithms Computer Aided Systems Theory - EUROCAST 2009, Lecture Notes in Computer Science, vol. 5717, pp. 729-736 Springer, 2009.

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S. Wagner Heuristic optimization software systems -Modeling of heuristic optimization algorithms in the HeuristicLab software environment Ph.D. thesis, Johannes Kepler University Linz, Austria, 2009.

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S. Wagner, A. Beham, G. Kronberger, M. Kommenda, E. Pitzer, M. Kofler, S. Vonolfen, S. Winkler, V. Dorfer, M. Affenzeller HeuristicLab 3.3: A unified approach to metaheuristic optimization Actas del séptimo congreso español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB'2010), 2010

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Detailed list of all publications of the HEAL research group: http://research.fh-ooe.at/de/orgunit/detail/356#showpublications

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Cited By

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Krynicki KJaen JEsparcia-Alcázar A(2015)AntElementsProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2768464(1109-1116)Online publication date: 11-Jul-2015
https://dl.acm.org/doi/10.1145/2739482.2768464
Kocsis ZBrownlee ASwan JSenington R(2015)Haiku - a Scala Combinator Toolkit for Semi-automated Composition of MetaheuristicsSearch-Based Software Engineering10.1007/978-3-319-22183-0_9(125-140)Online publication date: 28-Jul-2015
https://doi.org/10.1007/978-3-319-22183-0_9
Z-Flores ETrujillo LSchütze OLegrand P(2014)Evaluating the Effects of Local Search in Genetic ProgrammingEVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V10.1007/978-3-319-07494-8_15(213-228)Online publication date: 2014
https://doi.org/10.1007/978-3-319-07494-8_15

Index Terms

Algorithm and experiment design with heuristic lab: an open source optimization environment for research and education
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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Information

Published In

GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation

July 2012

1586 pages

ISBN:9781450311786

DOI:10.1145/2330784

Editor:
Terence Soule
University of Idaho, USA
,
General Chair:
Jason H. Moore
Dartmouth College, USA

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2012

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heuristiclab

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Tutorial

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GECCO '12

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SIGEVO

GECCO '12: Genetic and Evolutionary Computation Conference

July 7 - 11, 2012

Pennsylvania, Philadelphia, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Krynicki KJaen JEsparcia-Alcázar A(2015)AntElementsProceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation10.1145/2739482.2768464(1109-1116)Online publication date: 11-Jul-2015
https://dl.acm.org/doi/10.1145/2739482.2768464
Kocsis ZBrownlee ASwan JSenington R(2015)Haiku - a Scala Combinator Toolkit for Semi-automated Composition of MetaheuristicsSearch-Based Software Engineering10.1007/978-3-319-22183-0_9(125-140)Online publication date: 28-Jul-2015
https://doi.org/10.1007/978-3-319-22183-0_9
Z-Flores ETrujillo LSchütze OLegrand P(2014)Evaluating the Effects of Local Search in Genetic ProgrammingEVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V10.1007/978-3-319-07494-8_15(213-228)Online publication date: 2014
https://doi.org/10.1007/978-3-319-07494-8_15

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