Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms

Andreas Beham; Erik Pitzer; Stefan Wagner; Michael Affenzeller

doi:10.1007/978-3-319-74718-7_57

Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms

Andreas Beham, Erik Pitzer, Stefan Wagner, Michael Affenzeller

Research Center Hagenberg

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The no free lunch (NFL) theorem puts a limit to the range of problems a certain metaheuristic algorithm can be applied to successfully. For many methods these limits are unknown a priori and have to be discovered by experimentation. With the use of fitness landscape analysis (FLA) it is possible to obtain characteristic data and understand why methods perform better than others. In past research this data has been gathered mostly by a separate set of exploration algorithms. In this work it is studied how FLA methods can be integrated into the metaheuristic algorithm. We present a new exploratory method for obtaining landscape features that is based on path relinking (PR) and show that this characteristic information can be obtained faster than with traditional sampling methods. Path relinking is used in several metaheuristic which creates the possibility of integrating these features and enhance algorithms to output landscape analysis in addition to good solutions.

Original language	English
Title of host publication	Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers
Editors	Roberto Moreno-Diaz, Alexis Quesada-Arencibia, Franz Pichler
Pages	473-480
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-319-74718-7_57
Publication status	Published - 2018
Event	International Conference Computer Aided Systems Theory EUROCAST 2017 - Las Palmas de Gran Canaria, Spain Duration: 19 Feb 2017 → 24 Feb 2017 http://eurocast2017.fulp.ulpgc.es/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10671 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference Computer Aided Systems Theory EUROCAST 2017
Country/Territory	Spain
City	Las Palmas de Gran Canaria
Period	19.02.2017 → 24.02.2017
Internet address	http://eurocast2017.fulp.ulpgc.es/

Keywords

no free lunch
fitness landscape
heuristic algorithms

Access to Document

10.1007/978-3-319-74718-7_57

Cite this

Beham, A., Pitzer, E., Wagner, S., & Affenzeller, M. (2018). Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms. In R. Moreno-Diaz, A. Quesada-Arencibia, & F. Pichler (Eds.), Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers (pp. 473-480). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10671 LNCS). https://doi.org/10.1007/978-3-319-74718-7_57

Beham, Andreas ; Pitzer, Erik ; Wagner, Stefan et al. / Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms. Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. editor / Roberto Moreno-Diaz ; Alexis Quesada-Arencibia ; Franz Pichler. 2018. pp. 473-480 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The no free lunch (NFL) theorem puts a limit to the range of problems a certain metaheuristic algorithm can be applied to successfully. For many methods these limits are unknown a priori and have to be discovered by experimentation. With the use of fitness landscape analysis (FLA) it is possible to obtain characteristic data and understand why methods perform better than others. In past research this data has been gathered mostly by a separate set of exploration algorithms. In this work it is studied how FLA methods can be integrated into the metaheuristic algorithm. We present a new exploratory method for obtaining landscape features that is based on path relinking (PR) and show that this characteristic information can be obtained faster than with traditional sampling methods. Path relinking is used in several metaheuristic which creates the possibility of integrating these features and enhance algorithms to output landscape analysis in addition to good solutions.",

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Beham, A, Pitzer, E , Wagner, S & Affenzeller, M 2018, Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms. in R Moreno-Diaz, A Quesada-Arencibia & F Pichler (eds), Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10671 LNCS, pp. 473-480, International Conference Computer Aided Systems Theory EUROCAST 2017, Las Palmas de Gran Canaria, Spain, 19.02.2017. https://doi.org/10.1007/978-3-319-74718-7_57

Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms. / Beham, Andreas; Pitzer, Erik ; Wagner, Stefan et al.
Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. ed. / Roberto Moreno-Diaz; Alexis Quesada-Arencibia; Franz Pichler. 2018. p. 473-480 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10671 LNCS).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Beham A, Pitzer E , Wagner S , Affenzeller M. Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms. In Moreno-Diaz R, Quesada-Arencibia A, Pichler F, editors, Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. 2018. p. 473-480. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-74718-7_57

Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms

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