Hybrid PSO Algorithm with Iterated Local Search Operator for Equality Constraints Problems

Felipe O. Mota, Vinicius Almeida, Elizabeth Wanner, Gladston Moreira

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

This paper presents a hybrid PSO algorithm (Par-ticle Swarm Optimization) with an ILS (Iterated Local Search) operator for handling equality constraints problems in mono-objective optimization problems. The ILS can be used to locally search around the best solutions in some generations, exploring the attraction basins in small portions of the feasible set. This process can compensate the difficulty of the evolutionary algorithm to generate good solutions in zero-volume regions. The greatest advantage of the operator is the simple implementation. Experiments performed on benchmark problems shows improvement in accuracy, reducing the gap for the tested problems.
Original languageEnglish
Title of host publication2018 IEEE Congress on Evolutionary Computation (CEC)
PublisherIEEE
ISBN (Electronic)978-1-5090-6017-7
ISBN (Print)978-1-5090-6018-4
DOIs
Publication statusPublished - 4 Oct 2018
Event2018 IEEE Congress on Evolutionary Computation (CEC) - Rio de Janeiro, Brazil
Duration: 8 Jul 201813 Jul 2018

Conference

Conference2018 IEEE Congress on Evolutionary Computation (CEC)
CountryBrazil
CityRio de Janeiro
Period8/07/1813/07/18

Bibliographical note

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