【摘要】 基于对鱼、鸟群体捕食行为和过程的深入分析与系统研究,文章提出了一种改进的粒子群全局优化算法。主要内容包括:提出了粒子群初始化新机制以提高算法的收敛性能;引入了重启策略以避免算法陷于局部极值点或死循环;设计了全新的速度与位置矢量调节算法以提高优化方法的全局寻优能力。为验证前述工作的有效性和正确性,应用本文提出的改进粒子群算法对典型的数学函数和TEAM W orkshop问题22进行了分析和计算。计算结果表明:与原粒子群算法比较,本文算法的全局寻优能力明显提高。更多还原

【Abstract】 Based on a comprehensive simulation of bird flocking or fish schooling,an Improved Particle Swarm Optimization algorithm(IPSO) is proposed in this paper.The improvements include mainly the introduction of a new generating mechanism for initial particles to improve the convergence performances,the restarting strategy to avoid a stagnation phenomenon,and the design of novel velocity and position updating formulae to enhance the global search ability of the available PSOs.The numerical results on both a mathematical function and the TEAM Workshop problem obtained by using different optimization algorithms are reported and the performances are compared.Our numerical results suggest that the proposed IPSO algorithm is superior to its precursors in sense of the global search ability.更多还原