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https://hdl.handle.net/2440/83725
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Type: | Conference paper |
Title: | Population size matters: rigorous runtime results for maximizing the hypervolume indicator |
Author: | Nguyen, A. Sutton, A. Neumann, F. |
Citation: | Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, 2013 / C. Blum (eds.), pp.1613-1620 |
Publisher: | ACM |
Publisher Place: | online |
Issue Date: | 2013 |
ISBN: | 9781450319638 |
Conference Name: | Conference on Genetic and Evolutionary Computation (15th : 2013 : Amsterdam) |
Editor: | Blum, C. |
Statement of Responsibility: | Anh Quang Nguyen, Andrew M. Sutton, Frank Neumann |
Abstract: | Using the hypervolume indicator to guide the search of evolutionary multi-objective algorithms has become very popular in recent years. We contribute to the theoretical understanding of these algorithms by carrying out rigorous runtime analyses. We consider multi-objective variants of the problems OneMax and LeadingOnes called OMM and LOTZ, respectively, and investigate hypervolume-based algorithms with population sizes that do not allow coverage of the entire Pareto front. Our results show that LOTZ is easier to optimize than OMM for hypervolume-based evolutionary multi-objective algorithms which is contrary to the results on their single-objective variants and the well-studied (1+1)~EA. |
Keywords: | Multi-objective Optimization Theory Runtime Analysis |
Rights: | Copyright 2013 ACM |
DOI: | 10.1145/2463372.2463564 |
Description (link): | http://www.sigevo.org/gecco-2013/ |
Published version: | http://dx.doi.org/10.1145/2463372.2463564 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
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