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https://hdl.handle.net/2440/128927
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Type: | Journal article |
Title: | Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation |
Author: | Covantes Osuna, E. Gao, W. Neumann, F. Sudholt, D. |
Citation: | Theoretical Computer Science, 2018; 832:123-142 |
Publisher: | Elsevier BV |
Issue Date: | 2018 |
ISSN: | 0304-3975 1879-2294 |
Statement of Responsibility: | Edgar Covantes Osuna, Wanru Gao, Frank Neumann, Dirk Sudholt |
Abstract: | Parent selection in evolutionary algorithms for multi-objective optimisation is usually performed by dominance mechanisms or indicator functions that prefer non-dominated points. We propose to refine the parent selection on evolutionary multi-objective optimisation with diversity-based metrics. The aim is to focus on individuals with a high diversity contribution located in poorly explored areas of the search space, so the chances of creating new non-dominated individuals are better than in highly populated areas. We show by means of rigorous runtime analysis that the use of diversity-based parent selection mechanisms in the Simple Evolutionary Multi-objective Optimiser (SEMO) and Global SEMO for the well known bi-objective functions OneMinMax and LOTZ can significantly improve their performance. Our theoretical results are accompanied by experimental studies that show a correspondence between theory and empirical results and motivate further theoretical investigations in terms of stagnation. We show that stagnation might occur when favouring individuals with a high diversity contribution in the parent selection step and provide a discussion on which scheme to use for more complex problems based on our theoretical and experimental results. |
Keywords: | Parent selection; Evolutionary algorithms; Multi-objective optimisation; Diversity mechanisms; Runtime analysis; Theory |
Description: | Available online 19 June 2018 |
Rights: | © 2018 Elsevier B.V. All rights reserved. |
DOI: | 10.1016/j.tcs.2018.06.009 |
Grant ID: | http://purl.org/au-research/grants/arc/DP140103400 http://purl.org/au-research/grants/arc/DP160102401 |
Published version: | http://dx.doi.org/10.1016/j.tcs.2018.06.009 |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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