基于改进PSO和Tabu的混合算法
首发时间:2012-01-06
摘要:针对粒子群优化(PSO)算法在优化过程中容易早熟和局部寻优能力差,禁忌搜索(TS)算法依赖于初始解等问题,研究两者的优势和不足,通过改进PSO算法与TS算法混合,提出一种新型混合优化算法。通过采用引入随机扰动的PSO算法作全局搜索,禁忌搜索算法在得到PSO提供的优良初始解后作局部搜索。通过多种测试函数验证,该算法能有效克服PSO算法和TS算法的缺陷,使收敛精度有较大改进,并有效克服了早熟收敛问题。
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Hybrid Algorithm Based On Improved PSO And Tabu
Abstract:To deal with the prematurity and poor performance of local optimization of PSO algortithm and Tabu search depends strongly on its initial solution, and research the respective advantages and disadvantages between them, a novel hybrid algorithm is achieved through the improvement of PSO algrithm and mixture with TS algorithm.It use PSO which brings random perturbance do global search ,TS do local search atfer getting good initial solution from PSO.Simulation results of various function proved that this novel hybrid algorithm effectively overcomes the respective disadvantages of PSO algorithm and TS algorithm.It produces high convergence precision, and overcomes premature convergence effectively.
Keywords: Particle Swarm Optimization Tabu search Random perturbance Local Optima
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