Particle Swarm Based on Cultural Algorithm for Solving Constrained Optimization Problems

作者：Tongxi Li · 发表于：Jisuanji gongcheng · 年份：2008 · 被引用次数：5 · 研究领域：Metaheuristic Optimization Algorithms Research、Advanced Algorithms and Applications、Advanced Multi-Objective Optimization Algorithms

A Particle Swarm Optimization(PSO) based on cultural algorithm for solving constrained optimization problems is proposed. Thisalgorithm employs PSO using Gaussian and Cauchy probability distributions in population space, uses situational knowledge and normativeknowledge in belief space to guide the evolution of the population. In this way, it exploits the information sufficiently that the optimum individualcarries and speeds up the evolutionary process. Experimental results prove the algorithm is superior to basic PSO in quality and efficiency.