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Intelligent Parallel Particle Swarm Optimization Algorithms

  • Shu-Chuan Chu
  • Jeng-Shyang Pan
Part of the Studies in Computational Intelligence book series (SCI, volume 22)

Abstract

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.

Keywords

Particle Swarm Optimization Particle Swarm Particle Swarm Optimization Algorithm Communication Strategy Inertia Weight 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2006

Authors and Affiliations

  • Shu-Chuan Chu
    • 1
  • Jeng-Shyang Pan
    • 2
  1. 1.Department of Information ManagementCheng Shiu UniversityTaiwan
  2. 2.Department of Electronic EngineeringNational Kaohsiung University of Applied Sciences UniversityKaohsiung CityTaiwan

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