Particle Swarms Reformulated towards a Unified and Flexible Framework

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Abstract

The Particle Swarm Optimisation (PSO) algorithm has undergone countless modifications and adaptations since its original formulation in 1995. Some of these have become mainstream whereas many others have not been adopted and faded away. Thus, a myriad of alternative formulations have been proposed to the extent that the question arises as to what the basic features of an algorithm must be to belong in the PSO family. The aim of this paper is to establish what defines a PSO algorithm and to attempt to formulate it in such a way that it encompasses many existing variants. Therefore, different versions of the method may be posed as settings within the proposed unified framework. In addition, the proposed formulation generalises, decouples and incorporates features to the method providing more flexibility to the behaviour of each particle. The closed forms of the trajectory difference equation are obtained, different types of behaviour are identified, stochasticity is decoupled, and traditionally global features such as sociometries and constraint-handling are re-defined as particle's attributes.
Original languageEnglish
Title of host publicationProceedings of the Twelfth International Conference on Swarm Intelligence
PublisherSpringer Nature
Pages(In-Press)
Publication statusAccepted/In press - 30 Mar 2021
EventThe Twelfth International Conference on Swarm Intelligence - Virtual presentation permitted, Qingdao, China
Duration: 17 Jul 202121 Jul 2021
Conference number: 12
http://www.iasei.org/icsi2021/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature

Conference

ConferenceThe Twelfth International Conference on Swarm Intelligence
Abbreviated titleICSI 2021
CountryChina
CityQingdao
Period17/07/2121/07/21
Internet address

Bibliographical note

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