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An Analysis on the Effect of Selection on Exploration in PSO and DE (IEEE CEC 2019).pdf (337.2 kB)

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

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conference contribution
posted on 2023-05-23, 14:04 authored by Chen, S, Bolufe-Rohler, A, Erin MontgomeryErin Montgomery, Hendtlass, T
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.

History

Publication title

Proceedings of the 2019 IEEE Congress on Evolutionary Computation

Pagination

3037-3044

Department/School

School of Information and Communication Technology

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

United States

Event title

2019 IEEE Congress on Evolutionary Computation

Event Venue

Wellington, New Zealand

Date of Event (Start Date)

2019-06-10

Date of Event (End Date)

2019-06-13

Rights statement

Copyright 2019 IEEE

Repository Status

  • Open

Socio-economic Objectives

Expanding knowledge in the information and computing sciences

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