Parallel Evolutionary Computations

Volume 22 of the series Studies in Computational Intelligence pp 159-175

Intelligent Parallel Particle Swarm Optimization Algorithms

  • Shu-Chuan ChuAffiliated withDepartment of Information Management, Cheng Shiu University
  • , Jeng-Shyang PanAffiliated withDepartment of Electronic Engineering, National Kaohsiung University of Applied Sciences University

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Some social systems of natural species, such as flocks of birds and schools of fish, possess interesting collective behavior. In these systems, globally sophisticated behavior emerges from local, indirect communication amongst simple agents with only limited capabilities. In an attempt to simulate this flocking behavior by computers, Kennedy and Eberthart (1995) realized that an optimization problem can be formulated as that of a flock of birds flying across an area seeking a location with abundant food. This observation, together with some abstraction and modification techniques, led to the development of a novel optimization technique - particle swarm optimization.