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Research On Particle Swarm Optimization And Its Application

Posted on:2007-02-20Degree:DoctorType:Dissertation
Country:ChinaCandidate:K Y LeiFull Text:PDF
GTID:1118360185996403Subject:Basic Psychology
Abstract/Summary:PDF Full Text Request
Particle swarm optimization (PSO) is an evolutionary computation technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. Recently, PSO algorithm has been gradually attracted more attention over another intelligent algorithm. PSO is simple in concept, few in parameters, and easy in implementation. It was proved to be an efficient method to solve optimization problems, and has successfully been applied in the area of function optimization, neural network training and fuzzy control systems,etc. However, both theory and application of PSO are still far from mature.The dissertation focuses on the principles, theory, and application of PSO, especially, an in-deep and systemic study on how to improve the conventional PSO algorithm, solving the problems such as high-dimensional function optimization, multi-objective optimization (MO), path planning of robot, constrained layout optimization. The main achievements of this dissertation include:1. Considering the deficiencies of inertia weight of PSO, three functions, Sugeno (Yager ) function, Exponential function, SigmoidMF function, are proposed as inertia...
Keywords/Search Tags:evolutionary algorithm, particle swarm optimization, convergence analysis, premature problem, complex function, parameter selecting, multi-objective optimization, path planning, constrained layout optimization
PDF Full Text Request
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