计算机科学 ›› 2017, Vol. 44 ›› Issue (2): 250-256.doi: 10.11896/j.issn.1002-137X.2017.02.041
熊聪聪,郝璐萌,王丹,邓雪晨
XIONG Cong-cong, HAO Lu-meng, WANG Dan and DENG Xue-chen
摘要： 针对群搜索优化(Group Search Optimizer,GSO)算法易陷入局部最优、收敛速度较慢、收敛精度较低等问题,提出一种基于差分策略的群搜索优化(Differential Ranking-based Group Search Optimizer,DRGSO)算法。主要进行两方面改进:1)按照适应度值的大小对种群进行排序,适当增加发现者的数目,使种群能够获得更好的启发式信息,加快了算法的收敛速度,有效地避免了算法陷入局部最优；2)在发现者搜索过程中,引入4种不同的差分变异策略,提高了算法的收敛精度,增强了算法的群体多样性在。11组国际标准测试函数上的实验测试结果显示,与GA,GSO,PSO算法相比,DRGSO算法具有较强的全局搜索能力以及局部资源勘探能力,算法整体收敛性能明显提高。
| [1] HUANG W,OH S K,PEDRYCZ W.A space search optimization algorithm with accelerated convergence strategies [J].Applied Soft Computing,2013,13(12):4659-4675. [2] COLORNI A,DORIGO M,MANIEZZO V,et al.DistributedOptimization by Ant Colonies[C]∥Proceedings of the 1st European Conference on Artificial Life.Paris,France ,Elsevier Publishing,1991:134-142. [3] HUANG W,DING L X.The shortest path problem on a fuzzy time-dependent network [J].IEEE Transactions on Communications,2012,66(11):3376-3385. [4] HUANG Wei,OH S K,WITOLD P.Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs) [J].Neural Networks,2014,60:166-181. [5] HUANG W,DING L X.Project-Scheduling Problem with Random Time-Dependent Activity Duration Times [J].IEEE Transactions on Engineering Management,2011,58(2):377-387. [6] KENNEDY J,EBERHART R.Particle swarm optimization[C]∥IEEE International Conference on Neural Networks,1995.1995:1942-1948. [7] LI X L,SHAO Z J,QIAN J X.An Optimizing Method Based on Autonomous Animats:Fish-swarm Algorithm [J].System Engineering Theory and Practice,2002,22(11):32-38.(in Chinese) 李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式:鱼群算法[J].系统工程理论与实践,2002,2(11):32-38. [8] HE S,WU Q H,SAUNDERS J R.A Novel Group Search Optimizer Inspired by Animal Behavioural Ecology[C]∥IEEE Congress on Evolutionary Computation,2006(CEC 2006).IEEE,2006:1272-1278. [9] HE S,WU Q H,SAUNDERS J R.Group Search Optimizer:An Optimization Algorithm Inspired by Animal Searching Behavior [J].IEEE Transactions on Evolutionary Computation,2009,13(5):973-990. [10] WANG S W,DING L X,XIE D T,et al.Group Search Optimizer Applying Opposition-based Learning [J].Computer Science,2012,39(9):183-187.(in Chinese) 汪慎文,丁立新,谢大同,等.应用反向学习策略的群搜索优化算法[J].计算机科学,2012,39(9):183-187. [11] LIU F,QIN G,LI L J.A Quick Group Search Optimizer and Its Application Research [J].Engineering Mechanics,2010(7):38-44.(in Chinese) 刘锋,覃广,李丽娟.快速群搜索优化算法及其应用研究[J].工程力学,2010(7):38-44. [12] FANG J Y.Hybrid Group Search Optimizer and its Application [D].Taiyuan:Taiyuan University of Science and Technology,2010.(in Chinese) 房娟艳.混合群搜索优化算法及其应用研究[D].太原:太原科技大学,2010. [13] ZHANG W W,TENG S H,LI L J.Improved Group Search Optimizer algorithm [J].Computer Engineering and Applications,2009,45(4):48-51.(in Chinese) 张雯雾,滕少华,李丽娟.改进的群搜索优化算法[J].计算机工程与应用,2009,45(4):48-51. [14] WANG S W,DING L X,XIE C W,et al.Study on Role Assignment Strategies of Group Search Optimizer [J].Journal of Chinese Computer Systems,2012(9):1938-1943.(in Chinese) 汪慎文,丁立新,谢承旺,等.群搜索优化算法中角色分配策略的研究[J].小型微型计算机系统,2012(9):1938-1943. [15] LIU B,WANG L,JIN Y H.Advances in Differential Evolution [J].Control and Decision,2007,2(7):721-728.(in Chinese) 刘波,王凌,金以慧.差分进化算法研究进展[J].控制与决策,2007,2(7):721-728. [16] GONG W,CAI Z.Differential Evolution with Ranking-BasedMutation Operators [J].IEEE Transactions on Cybernetics,2013,43(6):2066-2081. [17] YANG Q W,CAI L,XUE Y C.A Survey of Differential Evolution Algorithms [J].Pattem Recognition and Aitificial Intelligence,2009,21(4):506-513.(in Chinese) 杨启文,蔡亮,薛云灿.差分进化算法综述[J].模式识别与人工智能,2009,21(4):506-513. [18] YAO X,LIU Y,LIN G.Evolutionary programming made faster [J].IEEE Transactions on Evolutionary Computation,1999,3(2):82-102. [19] SUN Y,LUO K.Clustering method based on improved particle swarm optimization [J].Computer Engineering and Applications,2009,45(33):132-134.(in Chinese) 孙洋,罗可.基于改进的粒子群算法的聚类算法[J].计算机工程与应用,2009,45(33):132-134. |
| No related articles found! |
|
||
首页