Article

Multiobjective hBOA, clustering, and scalability

Authors:

Martin Pelikan,

David E. GoldbergAuthors Info & Claims

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

Pages 663 - 670

https://doi.org/10.1145/1068009.1068122

Published: 25 June 2005 Publication History

Abstract

This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominated sorting genetic algorithm (NSGA-II) and clustering in the objective space. It is first argued that for good scalability, clustering or some other form of niching in the objective space is necessary and the size of each niche should be approximately equal. Multiobjective hBOA (mohBOA) is then described that combines hBOA, NSGA-II and clustering in the objective space. The algorithm mohBOA differs from the multiobjective variants of BOA and hBOA proposed in the past by including clustering in the objective space and allocating an approximately equally sized portion of the population to each cluster. The algorithm mohBOA is shown to scale up well on a number of problems on which standard multiobjective evolutionary algorithms perform poorly.

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https://dl.acm.org/doi/10.1145/3583131.3590403
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Multiobjective hBOA, clustering, and scalability

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cover image ACM Conferences

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

June 2005

2272 pages

ISBN:1595930108

DOI:10.1145/1068009

Editor:
Hans-Georg Beyer
Vorarlberg University of Applied Sciences, Austria
,
General Chair:
Una-May O'Reilly
CSAIL, MIT

Copyright © 2005 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: 25 June 2005

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June 25 - 29, 2005

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

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https://dl.acm.org/doi/10.1145/3583131.3590403
Liu SLin QLi JTan K(2023)A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective OptimizationIEEE Transactions on Evolutionary Computation10.1109/TEVC.2023.325035027:6(1941-1961)Online publication date: Dec-2023
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Guijt AThierens DAlderliesten TBosman PWagner M(2022)Solving multi-structured problems by introducing linkage kernels into GOMEAProceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528828(703-711)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1145/3512290.3528828
Jeong JLee ELee JAhn C(2022)Multi-Objective Deep Network-Based Estimation of Distribution Algorithm for Music CompositionIEEE Access10.1109/ACCESS.2022.318916310(71973-71985)Online publication date: 2022
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