基于单纯形法和自适应步长的花朵授粉算法  

A flower pollination algorithm based on simplex method and self-adaptive step

作　　者：肖辉辉[1,2] 

机构地区：[1]河池学院计算机与信息工程学院,广西宜州546300 [2]江西财经大学信息管理学院,江西南昌330013

出　　处：《计算机工程与科学》2016年第10期2126-2133,共8页Computer Engineering & Science

基　　金：国家自然科学基金(61173146);广西高校科研项目(KY2015LX332;KY2015LX334);校级项目(XJ2015QN003);河池学院"计算机网络与软件新技术"重点实验室(院科研【2013】3号);江西省研究生创新项目(YC2015-B054)

摘　　要：针对花朵授粉算法易陷入局部极值、后期收敛速度慢的不足,提出一种基于单纯形法和自适应步长的花朵授粉算法。该算法在基本花朵授粉算法的全局寻优部分采用自适应步长策略来更新个体位置,步长随迭代次数的增加而自适应地调整,避免局部极值;在局部寻优部分对进入下一次迭代的部分较差个体采用单纯形法的扩张、收缩/压缩操作,提高局部搜索能力,进而提高算法的寻优能力。通过八个CEC2005benchmark测试函数进行测试比较,结果表明,改进算法的寻优性能明显优于基本的花朵授粉算法,且其收敛速度、收敛精度、鲁棒性均较对比算法有较大提高。Aiming at the problems of easy falling into propose a self-adaptive step flower pollination algorithm local extremum and low convergence speed,we （FPA） based on the simplex method. We use the adaptive step length strategy to update individual location in the global optimization of the FPA,and the step is decreased dynamically along with the increase of iteration so that it can effectively avoid local optimum. In the process of local optimization of the FPA,to enhance the capacity of global optimization and improve the convergence speed,we perform expansion and contraction/compression operation of the simplex method on the weak individuals that enter the next iteration. The comparison and analysis of simulation results on the 8 CEC2005 benchmark functions show that the proposed algorithm has better global searching ability and robustness, and faster and more precise convergence than those of the basic flower pollination algorithms.

关 键 词：花朵授粉算法 寻优性能 单纯形法 自适应步长 适应度值 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]