other · 2023

Particle Swarm Optimization

Shafquat Rana, Md Sarwar, Anwar Shahzad Siddiqui, Prashant .

Cited by 54Open access

Abstract

Particle swarm optimization (PSO) has gained its importance over last 20 years and has been proven successful in many domains and disciplines of science and technology, as well as in other fields. It has shown its ability in optimizing various complex problems in a simpler way. Due to its simplicity and worldwide applications, the latest breakthroughs in PSO, as well as their applications in various fields are stated in this chapter. Its significance, algorithm and working mechanism along with the pseudo-code are presented in this chapter. The utility of PSO has been addressed and the flaws in the algorithm have been recognized. The recent advancements and modifications of PSO in terms of its parameters are also discussed. Finally, its hybridization with other illustrious algorithms and applications in multiple disciplines and domains over the last decades are discussed. The motivation for all hybrid optimization techniques is examined for real-world challenges. It has been noticed that PSO can be hybridized with other algorithms and parallel applications.

Cite this paper

APA 7

Rana, S., Sarwar, M., Siddiqui, A. S., & ., P. (2023). Particle Swarm Optimization. https://doi.org/10.1002/9781119906391.ch6

MLA 9

Rana, Shafquat, et al. “Particle Swarm Optimization.” 2023, pp. 95–113, https://doi.org/10.1002/9781119906391.ch6.

Chicago

Rana, Shafquat, Md Sarwar, Anwar Shahzad Siddiqui, and Prashant . 2023. “Particle Swarm Optimization.” https://doi.org/10.1002/9781119906391.ch6.

Harvard

Rana, S. et al. (2023) ‘Particle Swarm Optimization’. Available at: https://doi.org/10.1002/9781119906391.ch6.

BibTeX

@misc{rana2023particle,
  title = {{Particle Swarm Optimization}},
  author = {Rana, Shafquat and Sarwar, Md and Siddiqui, Anwar Shahzad and ., Prashant},
  pages = {95--113},
  year = {2023},
  doi = {10.1002/9781119906391.ch6}
}

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