PSO (Particle Swarm Optimization): One Method, Many Possible Applications

  • Cecconi F
  • Campenní M
N/ACitations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Particle Swarm Optimization (PSO) is an optimization technique, deriving from the EO [5]: the main features are the natural inspiration and the possibility to implement PSO onto different levels. This chapter is divided in three section: (1) the PSO definitions and relationship with MAS (Multi Agent Systems) framework; (2) three applications of PSO methods; (3) some general conclusions and perspectives. We try to show that PSO has a marked multidisciplinary character since systems with swarm characteristics can be observed in a variety of domains: the main argument in favor to PSO is proper the multidisciplinary character. Besides, POS can resolve multiobjective otpimization problems in efficient way, because POS naturally incorporates some concepts from Pareto-Optimal framework

Cite

CITATION STYLE

APA

Cecconi, F., & Campenní, M. (2010). PSO (Particle Swarm Optimization): One Method, Many Possible Applications (pp. 229–254). https://doi.org/10.1007/978-3-642-13425-8_11

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free