research-article

Initial-population bias in the univariate estimation of distribution algorithm

Authors:

Martin Pelikan,

Kumara SastryAuthors Info & Claims

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

Pages 429 - 436

https://doi.org/10.1145/1569901.1569961

Published: 08 July 2009 Publication History

Abstract

This paper analyzes the effects of an initial-population bias on the performance of the univariate marginal distribution algorithm (UMDA). The analysis considers two test problems: (1) onemax and (2) noisy onemax. Theoretical models are provided and verified with experiments. Intuitively, biasing the initial population toward the global optimum should improve performance of UMDA, whereas biasing the initial population away from the global optimum should have the opposite effect. Both theoretical and experimental results confirm this intuition. Effects of mutation on performance of UMDA with initial-population bias are also investigated.

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Cited By

Rodríguez R. JGarcía VEstrada L(2017)Algorithms for Attribute Selection and Knowledge DiscoveryKnowledge Management in Organizations10.1007/978-3-319-62698-7_33(399-409)Online publication date: 12-Jul-2017
https://doi.org/10.1007/978-3-319-62698-7_33
Ko SLim HKo HKim D(2016)Experimental comparisons with respect to the usage of the promising relations in EDA-based causal discoveryAnnals of Operations Research10.1007/s10479-016-2390-2265:2(241-255)Online publication date: 8-Dec-2016
https://doi.org/10.1007/s10479-016-2390-2
Davarynejad Mvan den Berg JRezaei J(2014)Evaluating center-seeking and initialization bias: The case of particle swarm and gravitational search algorithmsInformation Sciences10.1016/j.ins.2014.03.094278(802-821)Online publication date: Sep-2014
https://doi.org/10.1016/j.ins.2014.03.094
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Initial-population bias in the univariate estimation of distribution algorithm

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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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GECCO09: Genetic and Evolutionary Computation Conference

July 8 - 12, 2009

Québec, Montreal, Canada

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

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Cited By

Rodríguez R. JGarcía VEstrada L(2017)Algorithms for Attribute Selection and Knowledge DiscoveryKnowledge Management in Organizations10.1007/978-3-319-62698-7_33(399-409)Online publication date: 12-Jul-2017
https://doi.org/10.1007/978-3-319-62698-7_33
Ko SLim HKo HKim D(2016)Experimental comparisons with respect to the usage of the promising relations in EDA-based causal discoveryAnnals of Operations Research10.1007/s10479-016-2390-2265:2(241-255)Online publication date: 8-Dec-2016
https://doi.org/10.1007/s10479-016-2390-2
Davarynejad Mvan den Berg JRezaei J(2014)Evaluating center-seeking and initialization bias: The case of particle swarm and gravitational search algorithmsInformation Sciences10.1016/j.ins.2014.03.094278(802-821)Online publication date: Sep-2014
https://doi.org/10.1016/j.ins.2014.03.094
Rojas-Galeano SRodriguez NMoore J(2012)A memory efficient and continuous-valued compact EDA for large scale problemsProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330204(281-288)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330163.2330204
Klein AIshikawa FHoniden S(2011)Efficient Heuristic Approach with Improved Time Complexity for Qos-Aware Service CompositionProceedings of the 2011 IEEE International Conference on Web Services10.1109/ICWS.2011.60(436-443)Online publication date: 4-Jul-2011
https://dl.acm.org/doi/10.1109/ICWS.2011.60

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