Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 160-166.

• Intelligent Computing • Previous Articles     Next Articles

Differential Evolution Algorithm with Adaptive Population Size Reduction Based on Population Diversity

SHAN Tian-yu, GUAN Yu-yang   

  1. College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China
  • Online:2019-02-26 Published:2019-02-26

Abstract: To avoid premature effectively and improve the capability of global search,an algorithm named differential evolution algorithm with adaptive population size reduction based on population diversity(Dapr-DE) was proposed.Dapr-DE firstly uses population diversity to control the population size reduction.Then,Dapr-DE divides the population into some subpopulations by clustering and deletes the individuals according to their fitness,which keeps population diversity effectively and avoids local convergence.At last,the experimental results validate the effectiveness of the proposed algorithm on 30 real optimization problems in the CEC14 function set.

Key words: Clustering, Differential evolution algorithm, Heuristic algorithm, Population diversity

CLC Number: 

  • TP301
[1]STORN R,PRICE K.Differential Evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces:Technical Report:TR-95-012[R].1995.
[2]STORN R,PRICE K.Differential Evolution-A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces[J].Journal of Global Optimization,1997,11:341-359.
[3]MOIRANGTHEM J,KRISHNANAND K R,DASH S S,et al.Adaptive differential evolution algorithm for solving non-linear coordination problem of directional overcurrent relays[J].IET Generation,Transmission & Distribution,2013,7(4):329-336.
[4]WANG B C,LI H X,LI J P,et al.Composite Differential Evolution for Constrained Evolutionary Optimization[J].IEEE Tran-sactions on Systems,Man,and Cybernetics:Systems,2018,99:1-14.
[5]LAI J C,LEUNG F H,LING S H.A New Differential Evolution with self-terminating ability using fuzzy control and k-nearest neighbors[C]∥IEEE Congress on Evolutionary Computation.2010:1-8.
[6]LI S,SUN W.Optimization of fuzzy control rules based on differential evolution algorithm[C]∥Proceedings of 2014 IEEE Chinese Guidance,Navigation and Control Conference.2014:2610-2613.
[7]FENG X,SANDERSON A C,BONISSONE P P,et al.Fuzzy Logic Controlled Multi-Objective Differential Evolution[C]∥The 14th IEEE International Conference on Fuzzy Systems.2005:720-725.
[8]LIU L,YIN J T,ZHOU P T.Fault diagnosis of power transformer based on improved differential evolution-neural network[C]∥2013 IEEE 4th International Conference on Electronics Information and Emergency Communication.2013:238-241.
[9]BHATIA S,VISHWAKARMA V P.Feed forward neural network optimization using self adaptive differential evolution for pattern classification[C]∥2016 IEEE International Conference on Recent Trends in Electronics,Information & Communication Technology (RTEICT).2016:184-188.
[10]GOLDBERG D E.Genetic Algorithms in Search,Optimization,and Machine Learning[R].Addison-Wesley,Reading,MA,1989.
[11]MENGSHOEL O J,GOLDBERG D E.The crowding approach to niching in genetic algorithms[J].Evolutionary Computation,2008,16(3):315-354.
[12]SHI E C,LEUNG F H F,BONNIE N F.Differential Evolution with adaptive population size[C]∥Law 2014 19th International Conference on Digital Signal Processing.2014:876-881.
[13]BREST J,ZAMUDA A,FISTER I,et al.Large scale global optimization using self-adaptive differential evolution algorithm[C]∥Evolutionary Computation (CEC).2010:1-8.
[14]RONKKONEN J,KUKKONEN J,PRICE K V.Real-Parameter Optimization with Differential Evolution[C]∥The 2005 IEEE Congresson Evolutionary Computation.2005:506-513.
[15]PRICE K V,STORN R M,LAMPINEN J A.Differential Evolution,A Practical Approach to Global Optimization[R].Sprin-ger,2005.
[16]FEOKTISTOV V.Differential Evolution:In Search of Solutions (Springer Optimization and Its Applications)[R].Springer-Verlag NewYork,Inc.,Secaucus,NJ,USA,2006.
[17]VOLKOVAS R,FAIRBANK M,PEREZ-LIEBANA D.Diversity maintenance using a population of repelling random-mutation hill climbers[C]∥2017 9th Computer Science and Electronic Engineering (CEEC).2017:37-42
[18]CHEN L.An Adaptive Genetic Algorithm Based on Population Diversity Strategy[C]∥2009 Third International Conference on Genetic and Evolutionary Computing.2009:93-96.
[19]WAGSTAFF K,CARDIE C.Constrained K-means clustering with background knowledge[C]∥The Eighteenth International Conference on Machine Learning.2001:577-584.
[20]FREY B J,DUECK D.Clustering by Passing Messages Between Data Points[J].Science,2007,315:972-976.
[21]CUI X X,LI M,FANG T J.Study of population diversity of multiobjective evolutionary algorithm based on immune and entropy principles[C]∥Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat).2001:1316-1321.
[22]LIANG J J,QU B Y,SUGANTHAN P N.Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective realparameter numerical optimization[R].Tech.Rep.201311,Computational Intelligence Laboratory,Zhengzhou University,Zhengzhou,China,2014.
[23]LIU J,LAMPINEN J.A Fuzzy Adaptive Differential Evolution Algorithm[J].Soft Computing-A Fusion of Foundations,Me-thodologies and Applications,2005,9(6):448-462.
[24]ZHANG X,YE Z W,YANG J,et al.An approach for learning the optimal “tuned” masks based on differential evolution algorithm[C]∥2017 International Conference on Security,Pattern Analysis,and Cybernetics (SPAC).2017:585-590.
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