research-article

Effects of a deterministic hill climber on hBOA

Authors:

Elizabeth Radetic,

Martin Pelikan,

David E. GoldbergAuthors Info & Claims

GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation

Pages 437 - 444

https://doi.org/10.1145/1569901.1569962

Published: 08 July 2009 Publication History

Abstract

Hybridization of global and local search algorithms is a well-established technique for enhancing the efficiency of search algorithms. Hybridizing estimation of distribution algorithms (EDAs) has been repeatedly shown to produce better performance than either the global or local search algorithm alone. The hierarchical Bayesian optimization algorithm (hBOA) is an advanced EDA which has previously been shown to benefit from hybridization with a local searcher. This paper examines the effects of combining hBOA with a deterministic hill climber (DHC). Experiments reveal that allowing DHC to find the local optima makes model building and decision making much easier for hBOA. This reduces the minimum population size required to find the global optimum, which substantially improves overall performance.

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Cited By

Wang STung YYu T(2014)Investigation on efficiency of optimal mixing on various linkage sets2014 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2014.6900275(2475-2482)Online publication date: Jul-2014
https://doi.org/10.1109/CEC.2014.6900275
Chen WHsu CYu TChien WAlba E(2013)Effects of discrete hill climbing on model building forestimation of distribution algorithmsProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463418(367-374)Online publication date: 6-Jul-2013
https://dl.acm.org/doi/10.1145/2463372.2463418
Younes MKherfane R(2013)A new hybrid method for multi-objective economic power/emission dispatch in wind energy based power systemInternational Journal of System Assurance Engineering and Management10.1007/s13198-013-0208-z5:4(577-590)Online publication date: 5-Nov-2013
https://doi.org/10.1007/s13198-013-0208-z
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Effects of a deterministic hill climber on hBOA

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cover image ACM Conferences

GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation

July 2009

2036 pages

ISBN:9781605583259

DOI:10.1145/1569901

General Chair:
Franz Rothlauf
University of Mainz, Germany

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 July 2009

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July 8 - 12, 2009

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

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Cited By

Wang STung YYu T(2014)Investigation on efficiency of optimal mixing on various linkage sets2014 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2014.6900275(2475-2482)Online publication date: Jul-2014
https://doi.org/10.1109/CEC.2014.6900275
Chen WHsu CYu TChien WAlba E(2013)Effects of discrete hill climbing on model building forestimation of distribution algorithmsProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463418(367-374)Online publication date: 6-Jul-2013
https://dl.acm.org/doi/10.1145/2463372.2463418
Younes MKherfane R(2013)A new hybrid method for multi-objective economic power/emission dispatch in wind energy based power systemInternational Journal of System Assurance Engineering and Management10.1007/s13198-013-0208-z5:4(577-590)Online publication date: 5-Nov-2013
https://doi.org/10.1007/s13198-013-0208-z
Hauschild MPelikan MSastry KGoldberg D(2012)Using previous models to bias structural learning in the hierarchical boaEvolutionary Computation10.1162/EVCO_a_0005620:1(135-160)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1162/EVCO_a_00056
Bosman PThierens DLanzi P(2011)The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspectiveProceedings of the 13th annual conference companion on Genetic and evolutionary computation10.1145/2001858.2002065(663-670)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001858.2002065
Pelikan MCochran JCox LKeskinocak PKharoufeh JSmith J(2011)Genetic AlgorithmsWiley Encyclopedia of Operations Research and Management Science10.1002/9780470400531.eorms0357Online publication date: 14-Jan-2011
https://doi.org/10.1002/9780470400531.eorms0357
Luong HNguyen HAhn CPelikan MBranke J(2010)Entropy-based substructural local search for the bayesian optimization algorithmProceedings of the 12th annual conference on Genetic and evolutionary computation10.1145/1830483.1830547(335-342)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830483.1830547

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