Multi-method algorithms: Investigating the entity-to-algorithm allocation problem

This paper investigates the algorithm selection problem, otherwise referred to as the entity-to-algorithm allocation problem, within the context of three recent multi-method algorithm frameworks. A population-based algorithm portfolio, a meta-hyper-heuristic and a bandit based operator selection met...

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Bibliographic Details
Published in2013 IEEE Congress on Evolutionary Computation pp. 570 - 577
Main Authors Grobler, Jacomine, Engelbrecht, Andries P., Kendall, Graham, Yadavalli, V. S. S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2013
Subjects
Algorithm design and analysis
Heuristic algorithms
Optimization
Portfolios
Resource management
Sociology
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ISBN1479904538
9781479904532
ISSN1089-778X
DOI10.1109/CEC.2013.6557619

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Summary:This paper investigates the algorithm selection problem, otherwise referred to as the entity-to-algorithm allocation problem, within the context of three recent multi-method algorithm frameworks. A population-based algorithm portfolio, a meta-hyper-heuristic and a bandit based operator selection method are evaluated under similar conditions on a diverse set of floating-point benchmark problems. The meta-hyper heuristic is shown to outperform the other two algorithms.
ISBN:1479904538
9781479904532
ISSN:1089-778X
DOI:10.1109/CEC.2013.6557619