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Published in:
2006 | OriginalPaper | Chapter
Intelligent Parallel Particle Swarm Optimization Algorithms
Authors : Shu-Chuan Chu, Jeng-Shyang Pan
Published in: Parallel Evolutionary Computations
Publisher: Springer Berlin Heidelberg
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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.