• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 25 Issue 5
Oct.  2012
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Article Contents
LIU Zhigang, ZENG Jiajun, HAN Zhiwei. Adaptive Mutation Disturbance Particle Swarm Optimization Algorithm Based on Personal Best Position[J]. Journal of Southwest Jiaotong University, 2012, 25(5): 761-768. doi: 10.3969/j.issn.0258-2724.2012.05.006
Citation: LIU Zhigang, ZENG Jiajun, HAN Zhiwei. Adaptive Mutation Disturbance Particle Swarm Optimization Algorithm Based on Personal Best Position[J]. Journal of Southwest Jiaotong University, 2012, 25(5): 761-768. doi: 10.3969/j.issn.0258-2724.2012.05.006

Adaptive Mutation Disturbance Particle Swarm Optimization Algorithm Based on Personal Best Position

doi: 10.3969/j.issn.0258-2724.2012.05.006
  • Received Date: 08 May 2012
  • Publish Date: 25 Oct 2012
  • In order to overcome the disadvantage of the particle swarm optimization (PSO) that it easily falls into local optimum, an adaptive mutation disturbance particle swarm optimization (AMDPSO) algorithm based on personal best position was proposed. This algorithm is based on PSO, and the disturbance is considered. When the adaptive conditions are met, the mutation operation of particles is performed based on the personal best position. The proposed algorithm was applied to 6 test functions and compared with IWPSO (inertia weight particle swarm optimization), CFPSO (constriction factor particle swarm optimization) and DE (differential evolution). The research results show that the AMDPSO has a good convergence rate and optimization capability, and can easily escape the local optimum and keep the population diversity.

     

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  • 袁曾任. 人工神经网络及其应用[M]. 北京:清华大学出版社,1999: 2-5.
    COLORNI A, DORIGO M, MANIEZZO V, et al. Distributed optimization by ant colonies//Proceedings of the 1st European Conference on Artificial Life. Cambridge: MIT Press, 1992: 134-142.
    KIRKPATRICK S, GELATT C D, Jr. VECHIM M P. Optimization by simulated annealing[J]. Science, 1983, 220(4598): 671-680.
    HOLLAND J H. Adaptation in natural artificial systems[M]. Cambridge: MIT Press, 1975: 17.
    STORN R, PRICE K. Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. Berkley: International Computer Science Institute, 1995.
    KENNEDY J, EBETHART R C. Particle swam optimization//Proceedings of IEEE International Conference on Neural Networks. Perth: IEEE Press, 1995: 1942-1948.
    CHEN Debao, ZHAO Chunxia. Particle swarm optimization with adaptive population size and its application[J]. Applied Soft Computing, 2009, 9(1): 39-48.
    RATNAWEERA A, HALGAMUGE S K, WATSON H C. Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients[J]. IEEE Transactions on Evolutionary Computation, 2004, 8(3): 240-255.
    DU Jiyong, ZHANG Fengming, HUANG Guorong, et al. A new initializing mechanism in particle swarm optimization //2011 IEEE International Conference on Computer Science and Automation Engineering(CSCA). Shanghai: IEEE Press, 2011, 4: 325-329.
    胡广浩,毛志忠,何大阔. 基于两阶段领导的多目标粒子群优化算法[J]. 控制与决策,2010,25(3): 404-415. HU Guanghao, MAO Zhizhong, HE Dakuo. Multi-objective PSO optimization algorithm based on two stages guided[J]. Control and Decision, 2010, 25(3): 404-415.
    曾嘉俊,刘志刚,黄元亮,等. 基于子区域的粒子群优化算法研究[J]. 计算机工程,2011,37(14): 205-208. ZENG Jiajun, LIU Zhigang, HUANG Yuanliang, et al. Research of particle swarm optimization algorithm based on sub-region[J]. Computer Engineering, 2011, 37(14): 205-208.
    迟玉红,孙富春,王维军,等. 基于空间缩放和吸引子的粒子群优化算法[J]. 计算机学报,2011,34(1): 115-130. CHI Yuhong, SUN Fuchun, WANG Weijun, et al. An improved particle swarm optimization algorithm with search space zoomed factor and attractor[J]. Chinese Journal of Computers, 2011, 34(1): 115-130.
    池元杰,方杰,魏鑫,等. 基于小生境和交叉选择算子的改进粒子群优化算法[J]. 系统仿真学报,2010,22(1): 111-114. CHI Yuanjie, FANG Jie, WEI Xin, et al. Improved particle swarm optimization algorithm based on niche, crossover and selection operators[J]. Journal of System Simulation, 2010, 22(1): 111-114.
    SUN Jun, FENG Bin,XU Wenbo. Particle swarm optimization with particles having quantum behavior//Congress Evolutionary Computation. Portland: IEEE Press, 2004, 1: 325-331.
    SHA Y D, HSU C Y. A hybrid particle swarm optimization for job shop scheduling problem[J]. Computers and Industrial Engineering, 2006, 51(4): 791-808.
    ZHOU Dawei, GAO Xiang, LIU Guohai, et al. Randomization in particle swarm optimization for global search ability[J]. Expert Systems with Applications, 2011, 38(12): 15356-15364.
    唐贤伦. 混沌粒子群优化算法理论及应用研究. 重庆:重庆大学,2007.
    刘东,冯全源,蒋启龙. 基于改进PSO算法的磁浮列车PID控制器参数优化[J]. 西南交通大学学报,2010,45(3): 405-410. LIU Dong, FENG Quanyuan, JIANG Qilong. Parameter optimization of maglev PID controller based on improved PSO algorithm[J]. Journal of Southwest Jiaotong University, 2010, 45(3): 405-410.
    郭惠勇,王磊,李正良. 基于改进粒子群算法的两阶段损伤识别方法[J]. 西南交通大学学报,2011,46(6): 926-932. GUO Huiyong, WANG Lei, LI Zhengliang. Two-stage damage detection method based on improved particle swarm optimization algorithm[J]. Journal of Southwest Jiaotong University, 2011, 46(6): 926-932.
    SHI Y, EBERHART R C. A modified particle swarm optimizer//Proceedings of the 1998 Conference of Evolutionary Computation. Anchorage: IEEE Press, 1998: 69-73.
    吕振肃,侯志荣. 自适应变异的粒子群优化算法[J]. 电子学报,2004,32(3): 416-420. LÜ Zhensu, HOU Zhirong. Particle swarm optimization with adaptive mutation[J]. Acta Electronica Sinica, 2004, 32(3): 416-420.
    CLERC M, KENNEDY J. The particle swarm-explosion, stability, and convergence in a multidimensional complex space[J]. IEEE Transaction on Evolutionary Computation, 2002, 6(1): 58-73.
    付国江,王少梅,刘舒燕,等. 含边界变异的粒子群算法[J]. 武汉理工大学学报,2005,27(9): 101-103. FU Guojiang, WANG Shaomei, LIU Shuyan, et al. A PSO with bounded mutation operator[J]. Journal of Wuhan University of Technology, 2005, 27(9): 101-103.
    胡旺,李志蜀. 一种更简化而高效的粒子群优化算法[J]. 软件学报,2007,18(4): 861-868. HU Wang, LI Zhishu. A simpler and more effective particle swarm optimization algorithm[J]. Journal of Software, 2007, 18(4): 861-868.
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