关键词: 随机性优化算法, 有效性评价, 粒子群优化算法

Abstract: To compare effectiveness of different stochastic optimization algorithms quantitatively, a method is proposed, which is based on statistical analysis of multiple independent results of those algorithms solving a set of typical test samples. Probability quantifying the relative superiority of effectiveness of two algorithms is conducted. Using this method, effectiveness comparison of different stochastic optimization algorithms is easy to make. Further, this method is implemented on two patterns of standard Particle Swarm Optimization（PSO） algorithm, in which the global best particle’s information is updated synchronously as well as asynchronously. As a result, a relatively effective pattern of standard PSO algorithm solving unconstrained single-objective optimization problems is advised.

Key words: stochastic optimization algorithm, effectiveness comparison, Particle Swarm Optimization（PSO）