conference paper
Particle swarm optimization
James Kennedya, Russell C. Eberhartb
- aWashington D.C., DC, USA
- bPurdue School of Engineering and Technology, Indianapolis, IN, USA
2002-11-19 58K citations11 references
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Abstract
A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.