Particle Swarm Optimization: The Foundation
Dadabada Pradeep Kumar
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Dadabada Pradeep Kumar: Indian Institute of Management Shillong
Chapter Chapter 6 in Applying Particle Swarm Optimization, 2021, pp 97-110 from Springer
Abstract Particle swarm optimization (PSO) is a very much popular swarm intelligence algorithm. Since its inception in the year 1995, it is being applied to solve optimization problems in many domains, including portfolio optimization. This chapter lays the basic PSO foundation and introduces existing PSO variants for researchers who want to solve the portfolio optimization problem. It starts with the introduction of PSO, describing the advantages, disadvantages, and applied areas of PSO. Later, the basic PSO procedure and its parameter selection mechanisms are presented. The chapter also presents three popular applications of PSO in finance, including portfolio optimization. Finally, the chapter ends by introducing the existing PSO variants to solve the portfolio optimization problem.
Keywords: Portfolio optimization; PSO algorithm; Applications; Fitness; Position update; Velocity update; Swarm intelligence (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-70281-6_6
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