A note on the exclusion operator in multi-swarm PSO algorithms for dynamic environments. Issue 3 (2nd July 2020)

• Record Type: Journal Article
• Authors: Kazemi Kordestani, Javidan; Meybodi, Mohammad Reza; Rahmani, Amir Masoud
• Is Part Of: Connection science. Volume 32:Issue 3(2020)
• Page Start: 239
• Page End: 263
• Publication Date: 2020-07-02
• Subjects: Exclusion -- dynamic optimisation problems -- multi-swarm PSO -- multi-population methods -- moving peaks benchmark; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2019.1700912
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : The exclusion operator is a key component in separating the search territory of each population in multi-population optimisation algorithms for unconstraint continues dynamic optimisation problems (DOPs) with the aim of maintaining the overall diversity of the population and avoiding redundant search. Although extensively used by the researchers, the role of exclusion has been barely studied in detail. Therefore, in this paper, we solely study the role of exclusion as a part of multi-population methods in DOPs. For this purpose, a comprehensive review of the various exclusion strategies reported in the literature is provided. Four strategies are also introduced to reduce the shortcomings of exclusion operator. Experimental results show that proposed strategies compared to other schemes such as reinitialized midpoint check, hill-valley detection with three checkpoints, and merging information of collided populations have the same or even higher ability to improve the performance of the multi-swarm PSO algorithms in moving peaks benchmark.