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An analysis on the effect of selection on exploration in particle swarm optimization and differential evolution


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Chen, S, Bolufe-Rohler, A, Montgomery, J ORCID: 0000-0002-5360-7514 and Hendtlass, T 2019 , 'An analysis on the effect of selection on exploration in particle swarm optimization and differential evolution', paper presented at the 2019 IEEE Congress on Evolutionary Computation, 10-13 June 2019, Wellington, New Zealand.

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The goal of exploration to produce diverse search points throughout the search space can be countered by the goal of selection to focus search around the fittest current solution(s). In the limit, if all exploratory search points are rejected by selection, then the behaviour of the metaheuristic will be equivalent to one which performs no exploration at all (e.g. hill climbing). The effects of selection on exploration are clearly important, but our review of the literature indicates limited coverage. To address this deficit, we introduce new experiments which can specifically highlight the occurrence of “failed exploration” and its effects through selection that can trap a metaheuristic in a less promising part of the search space. We subsequently propose new lines of research to reduce the effects of selection and failed exploration which we believe are distinctly different from traditional lines of research to increase (pre-selection) exploration.

Item Type: Conference or Workshop Item (Paper)
Authors/Creators:Chen, S and Bolufe-Rohler, A and Montgomery, J and Hendtlass, T
Keywords: exploration, selection, metaheuristics, continuous domain search spaces
Journal or Publication Title: Proceedings of the 2019 IEEE Congress on Evolutionary Computation
Publisher: Institute of Electrical and Electronics Engineers
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Copyright 2019 IEEE

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