Chaos embedded particle swarm optimization algorithms

摘要: Abstract This paper proposes new particle swarm optimization (PSO) methods that use chaotic maps for parameter adaptation. has been done by using of number generators each time a random is needed the classical PSO algorithm. Twelve chaos-embedded have proposed and eight analyzed in benchmark functions. It detected coupling emergent results different areas, like those complex dynamics, can improve quality some problems. also shown that, somewhat increased solution quality, cases they improved global searching capability escaping local solutions.