eCite Digital Repository

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

Citation

Chen, S and Bolufe-Rohler, A and Montgomery, J and Hendtlass, T, An analysis on the effect of selection on exploration in particle swarm optimization and differential evolution, Proceedings of the 2019 IEEE Congress on Evolutionary Computation, 10-13 June 2019, Wellington, New Zealand, pp. 3038-3045. (2019) [Refereed Conference Paper]


Preview
PDF (Author's final version)
337Kb
  

Copyright Statement

Copyright 2019 IEEE

Official URL: http://dx.doi.org/10.1109/CEC.2019.8790200

Abstract

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 Details

Item Type:Refereed Conference Paper
Keywords:exploration, selection, metaheuristics, continuous domain search spaces
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Information and Computing Sciences
UTAS Author:Montgomery, J (Dr James Montgomery)
ID Code:132154
Year Published:2019
Deposited By:Information and Communication Technology
Deposited On:2019-04-24
Last Modified:2019-10-23
Downloads:2 View Download Statistics

Repository Staff Only: item control page