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Genetic algorithm assisted HIDMS-PSO: a new hybrid algorithm for global optimisation

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conference contribution
posted on 2023-06-10, 00:40 authored by Fevzi Tugrul Varna, Phil HusbandsPhil Husbands
In this paper, a new hybrid algorithm, GA-HIDMS-PSO, is introduced by hybridising the state-of-the-art particle swarm optimisation (PSO) variant, the heterogeneous improved dynamic multi-swarm PSO (HIDMS-PSO) with a genetic algorithm (GA). The new hybrid model exploits the heterogeneous features of HIDMS-PSO and the evolutionary characteristics of the GA. In the GA-HIDMS-PSO architecture, HIDMS-PSO acts as the primary search engine, and the GA is employed as the secondary method to assist and slow down the loss of diversity for selected proportions of homogeneous and heterogeneous subpopulations of the HIDMS-PSO algorithm. Both methods run consecutively. As the primary search method, HIDMS-PSO runs for longer periods compared with the GA. The HIDMS-PSO pro-vides the initial solutions for the GA from both homogeneous and heterogeneous subpopulations and final solutions returned from the GA replace prior solutions in the HIDMS-PSO which resumes the search process with potentially more diverse particles to guide the swarm. The GA-HIDMS-PSO algorithm’s performance was tested on the 30 and 50 dimensional CEC’05 and CEC’17 test suites. The results were compared with 24 algorithms, with 12 state-of-the-art PSO variants and 12 other metaheuristics. GA-HIDMS-PSO outperformed all 24 comparison algorithms on both test suites for both 30 and 50 dimensions.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Proceedings of IEEE Congress on Evolutionary Computation (CEC)

Publisher

IEEE

Page range

1304-1311

Event name

IEEE CEC 2021

Event location

Kraków, Poland

Event type

conference

Event date

28th June - 1st July 2021

ISBN

9781728183947

Department affiliated with

  • Informatics Publications

Research groups affiliated with

  • Centre for Computational Neuroscience and Robotics Publications

Notes

© 2021 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

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2021-08-19

First Open Access (FOA) Date

2021-08-19

First Compliant Deposit (FCD) Date

2021-08-19

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