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

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.

Publication DOI: https://doi.org/10.1109/CEC.2018.8477884
Divisions: College of Engineering & Physical Sciences
Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Event Title: 2018 IEEE Congress on Evolutionary Computation (CEC)
Event Type: Other
Event Dates: 2018-07-08 - 2018-07-13
ISBN: 978-1-5090-6018-4, 978-1-5090-6017-7
Full Text Link:
Related URLs: https://ieeexpl ... ocument/8477884 (Publisher URL)
PURE Output Type: Conference contribution
Published Date: 2018-10-04
Accepted Date: 2018-05-01
Authors: Mota, Felipe O.
Almeida, Vinicius
Wanner, Elizabeth (ORCID Profile 0000-0001-6450-3043)
Moreira, Gladston

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