基于发现者预选择机制的自适应群搜索算法  

Producer pre-selection mechanism based on self-adaptive group search optimizer

作　　者：于长青[1] 王竹荣[1] 

机构地区：[1]西安理工大学计算机科学与工程学院,西安710048

出　　处：《计算机应用》2013年第11期3102-3106,共5页journal of Computer Applications

基　　金：陕西省教育厅科学研究计划项目(2013JK1185)

摘　　要：为克服群搜索(GSO)算法早熟的缺点,提高算法收敛速度,提出一种基于发现者预选择机制的自适应群搜索(PSAGSO)算法。首先,依据发现者-追随者模型,采用预选择机制,用倒序变异算子产生新发现者,来引导追随者寻优的方向,有效地维持了群体中个体的多样性;其次,提出一种基于线性递减的动态自适应方法来调整游荡者的分布比例,以提高种群中个体的活力,有利于算法跳出局部最优。通过对12个基准函数进行测试。对于30维函数优化,PSAGSO算法的测试数据优于He等(HE S,WU Q H,SAUNDERS J R.Group search optimizer:an optimization algorithm inspired by animal searching behavior.IEEE Transactions on Evolutionary Computation,2009,13(5):973-990)提供的数据;对于300维函数优化问题,PSAGSO算法的性能更佳。实验结果表明,PSAGSO克服了群搜索优化算法的不足,在一定程度上提高了算法的收敛速度和收敛精度。To overcome the prematurity of Group Search Optimizer （GSO） and improve its convergence speed, a producer pre-seleetion mechanism based self-adaptive group search optimizer （PSAGSO） algorithm was proposed. Firstly, the reverse mutation operator and pre-selection mechanism were employed to generate a new producer by producer-scrounger model to guide the search directions of scrounger and effectively maintain the diversity of population. Secondly, a self-adaptive method based on linear decreasing weight was adopted to adjust the proportion of rangers, which is to improve individual vigor of the population and benefit to escape from local optima. Experiments were conducted on a set of 12 benchmark functions. For 30- dimensional function optimization, the test data obtained by the PSAGSO algorithm was better than that in the literature （ HE S, WU Q H, SAUNDERS J R. Group search optimizer： an optimization algorithm inspired by animal searching behavior. IEEE Transactions on Evolutionary Computation, 2009, 13（ 5）： 973 -990）. For 300-dimensional numerical optimization problems, the PSAGSO algorithm exhibited better performance. The experimental result demonstrates that the PSAGSO algorithm improves the group search optimizer, and to some extent it improves the algorithm convergence speed and accuracy.

关 键 词：群智能算法 群搜索算法 预选择机制 倒序变异 自适应方法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]