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Particle Swarm Optimization: The Foundation

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Applying Particle Swarm Optimization

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 306))

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.

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Authors and Affiliations

  1. Area of Information Systems and Analytics, Indian Institute of Management Shillong, Shillong, Meghalaya, India

    Dadabada Pradeep Kumar

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  1. Faculty of Transportation and Logistics, Istanbul University, Avcılar/Istanbul, Turkey

    Burcu Adıgüzel Mercangöz

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Kumar, D.P. (2021). Particle Swarm Optimization: The Foundation. In: Mercangöz, B.A. (eds) Applying Particle Swarm Optimization. International Series in Operations Research & Management Science, vol 306. Springer, Cham. https://doi.org/10.1007/978-3-030-70281-6_6

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