Computer Science ›› 2017, Vol. 44 ›› Issue (2): 250-256.doi: 10.11896/j.issn.1002-137X.2017.02.041

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Group Search Optimizer Based on Differential Strategies

XIONG Cong-cong, HAO Lu-meng, WANG Dan and DENG Xue-chen   

  • Online:2018-11-13 Published:2018-11-13

Abstract: The conventional group search optimizer (GSO) is not free from some drawbacks such as easily falling into local optimum,a relative long computing time and lower convergence accuracy.In this study,we proposed a differential ranking-based group search optimizer (DRGSO) algorithm to alleviate these limitations.There are mainly two improvements in the design of DRGSO.First,the population is initialized according to the ranking of fitness values.With this regard,the population obtains heuristic information and alleviates premature convergence to some extent.Second,four evolutionary operators based on differential strategies are constructed to improve the convergence of the algorithm and enhance the population diversity.To demonstrate the performance,eleven benchmark functions were included to eva-luate the performance of DRGSO.Experimental results indicate that the proposed DRGSO exhibits better performance in comparison with the GA,PSO and GSO in terms of accuracy and speed of convergence.

Key words: Group search optimizer (GSO),Differential mutation,Convergence speed,Convergence accuracy

[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.

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