Niching Without Niching Parameters: Particle Swarm Optimization Using a Ring Topology

• Published in: IEEE transactions on evolutionary computation Vol. 14; no. 1; pp. 150 - 169
• Main Author: Li, Xiaodong
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Artificial intelligence; Australia; Computer science; Computer science; control theory; systems; Evolutionary algorithms; Evolutionary computation; Exact sciences and technology; Information technology; Learning and adaptive systems; Machine learning; multimodal optimization; Network topology; Networks; niching algorithms; Optimization; Optimization methods; Particle swarm optimization; particle swarm optimization (PSO); Robustness; Searching; Space exploration; Specifications; swarm intelligence; Topology; Local search; niching algorithms; Evolutionary algorithm; Evolutionary computation; Neural network; Topology; Experimental study; Particle swarm optimization; Search algorithm; multimodal optimization; Ring; Ecological niche; Population size; Swarm intelligence; Localization; particle swarm optimization (PSO); Artificial intelligence

Niching is an important technique for multimodal optimization. Most existing niching methods require specification of certain niching parameters in order to perform well. These niching parameters, often used to inform a niching algorithm how far apart between two closest optima or the number of opti...