一种拟随机初始化模拟退火粒子群算法A Quasi-randomized Initialized Simulated Annealing Particle Swarm Optimization Algorithm
王杰,李慧慧,彭金柱
摘要(Abstract)：
针对粒子群优化算法在求解高维问题时易出现的早熟收敛、停滞现象,提出一种拟随机初始化模拟退火粒子群算法.采用Hammersley方法对算法进行初始化,可以提高算法在高维搜索空间的搜索能力,进一步将模拟退火思想引入到粒子群优化算法中,结合粒子群优化算法的快速寻优能力和模拟退火算法的概率突跳特性,使算法具有跳出局部最优从而实现全局最优的能力.分别在5个经典测试函数上测试算法的性能,仿真实验结果表明,提出的算法有效克服了传统粒子群优化算法在求解高维空间优化问题时易出现的停滞现象,在进化后期仍保持较强的搜索能力,提高了传统粒子群优化算法在高维空间的全局寻优能力.
关键词(KeyWords)： 拟随机序列;初始化;模拟退火;粒子群优化
基金项目(Foundation): 教育部高等学校博士学科点专项科研基金资助项目(20124101120001);; 河南省教育厅科学技术研究重点项目(14A413009);; 中国博士后科学基金资助项目(2014T70685)
作者(Author): 王杰,李慧慧,彭金柱
DOI: 10.13705/j.issn.1671-6841.2016022
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