A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain

Swarm Intelligence (SI) is one of the research fields that has continuously attracted researcher attention in these last two decades. The flexibility and a well-known decentralized collective behavior of its algorithm make SI a suitable candidate to be implemented in the swarm robotics domain for re...

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Bibliographic Details
Published in:Archives of Computational Methods in Engineering
Main Author: Hamami M.G.M.; Ismail Z.H.
Format: Review
Language:English
Published: Springer Science and Business Media B.V. 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139628569&doi=10.1007%2fs11831-022-09819-3&partnerID=40&md5=783c166b023b66f2a481a3aa87f32c31
id 2-s2.0-85139628569
spelling 2-s2.0-85139628569
Hamami M.G.M.; Ismail Z.H.
A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
2022
Archives of Computational Methods in Engineering


10.1007/s11831-022-09819-3
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139628569&doi=10.1007%2fs11831-022-09819-3&partnerID=40&md5=783c166b023b66f2a481a3aa87f32c31
Swarm Intelligence (SI) is one of the research fields that has continuously attracted researcher attention in these last two decades. The flexibility and a well-known decentralized collective behavior of its algorithm make SI a suitable candidate to be implemented in the swarm robotics domain for real-world optimization problems such as target search tasks. Since the introduction of Particle Swarm Optimization (PSO) as a representation of the SI algorithm, it has been widely accepted and utilized especially in local and global search strategies. Because of its simplicity, effectiveness, and low computational cost, PSO has retained popularity notably in the swarm robotics domain, and many improvements have been proposed. Target search problems are one of the areas that have been continuously solved by PSO. This article set out to analyze and give the inside view of the existing literature on PSO strategies towards target search problems. Based on the procedure of PRISMA Statement review method, a systematic review identified 51 related research studies. After further analysis of these total 51 selected articles and consideration on the PSO components, target search components, and research field components, resulting in nine main elements related to the discussed topic. The elements are PSO variant, application field, PSO inertial weight function, PSO efficiency improvement, PSO termination criteria, target available, target mobility status, experiment framework, and environment complexity. Several recommendations, opinions, and perfectives on the discussed topic are presented. Finally, recommendations for future research in this domain are represented to support future developments. © 2022, The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE).
Springer Science and Business Media B.V.
11343060
English
Review
All Open Access; Bronze Open Access; Green Open Access
author Hamami M.G.M.; Ismail Z.H.
spellingShingle Hamami M.G.M.; Ismail Z.H.
A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
author_facet Hamami M.G.M.; Ismail Z.H.
author_sort Hamami M.G.M.; Ismail Z.H.
title A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
title_short A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
title_full A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
title_fullStr A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
title_full_unstemmed A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
title_sort A Systematic Review on Particle Swarm Optimization Towards Target Search in The Swarm Robotics Domain
publishDate 2022
container_title Archives of Computational Methods in Engineering
container_volume
container_issue
doi_str_mv 10.1007/s11831-022-09819-3
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139628569&doi=10.1007%2fs11831-022-09819-3&partnerID=40&md5=783c166b023b66f2a481a3aa87f32c31
description Swarm Intelligence (SI) is one of the research fields that has continuously attracted researcher attention in these last two decades. The flexibility and a well-known decentralized collective behavior of its algorithm make SI a suitable candidate to be implemented in the swarm robotics domain for real-world optimization problems such as target search tasks. Since the introduction of Particle Swarm Optimization (PSO) as a representation of the SI algorithm, it has been widely accepted and utilized especially in local and global search strategies. Because of its simplicity, effectiveness, and low computational cost, PSO has retained popularity notably in the swarm robotics domain, and many improvements have been proposed. Target search problems are one of the areas that have been continuously solved by PSO. This article set out to analyze and give the inside view of the existing literature on PSO strategies towards target search problems. Based on the procedure of PRISMA Statement review method, a systematic review identified 51 related research studies. After further analysis of these total 51 selected articles and consideration on the PSO components, target search components, and research field components, resulting in nine main elements related to the discussed topic. The elements are PSO variant, application field, PSO inertial weight function, PSO efficiency improvement, PSO termination criteria, target available, target mobility status, experiment framework, and environment complexity. Several recommendations, opinions, and perfectives on the discussed topic are presented. Finally, recommendations for future research in this domain are represented to support future developments. © 2022, The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE).
publisher Springer Science and Business Media B.V.
issn 11343060
language English
format Review
accesstype All Open Access; Bronze Open Access; Green Open Access
record_format scopus
collection Scopus
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