1.College of Information Science and Engineering,Guangxi University for Nationalities,Nanning 530006 2.Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis,Guangxi University for Nationalities,Nanning 530006 3.School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044
Abstract Pattern search algorithm often falls into local optimization and its efficiency is low. Inspired by swarm intelligence algorithm,a global optimization algorithm,swarm pattern global search algorithm (SPGSA),is proposed. Swarm intelligence is introduced to SPGSA in the evolution process. Thus,SPGSA includes pattern search operator,pattern moving operator,pattern learning operator and pattern dispersion operator.It has a strong ability of global and local search as well as better features of fast convergence and good stability. Comparisons of the simulation results by using standard benchmark functions prove the effectiveness.
[1] Vaz A I,Vicente L N. A Particle Swarm Pattern Search Method for Bound Constrained Global Optimization. Journal of Global Optimization,2007,39(2): 197-219 [2] Feng Yuanjing,Yu Li,Feng Zuren. Ant Colony Pattern Search Algorithms and Their Convergence. Control Theory Applications,2007,24(6): 943-948(in Chinese) (冯远静,俞 立,冯祖仁.蚁群协同模式搜索算法及其收敛性分析.控制理论与应用,2007,24(6): 943-948) [3] Hooke R,Jeeves T A. Direct Search Solution of Numerical and Statistical Problems. Journal of ACM,1961,8(2): 212-229 [4] Liu Chun′an ,Wang Yuping. Evolutionary Algorithm for Constrained Multi-Objective Optimization Problems and Its Convergence. Systems Engineering and Electronics,2007,29(2): 276-280(in Chinese) (刘淳安,王宇平.约束多目标优化问题的进化算法及其收敛性.系统工程与电子技术,2007,29(2): 276-280) [5] Xu Zongben,Zhang Jiangshe,Zheng Yalin. Bionics in Computational Intelligence: Theory and Algorithms. Beijing,China: Science and Technology Press,2003(in Chinese) (徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法.北京:科技出版社,2003) [6] Back T. Evolutionary Algorithms in Theory and Practice. Oxford,UK: Oxford University Press,1996 [7] Ma Haipin,Li Huan,Ruan Xieyong. Species Migration-Based Optimization Algorithm and Performance Analysis. Control Theory Applications,2010,27(3): 329-334(in Chinese) (马海平,李 寰,阮谢永.一种群体迁移优化算法及性能分析.控制理论与应用,2010,27(3): 329-334) [8] Dorigo M,Gambadella L M,Middendorf M,et al. Guest Editorial: Special Section on Ant Colony Optimization. IEEE Trans on Evolutionary Computation,2002,6(4): 317-319 [9] Mezura-Montes E,Coello C A C. A Simple Multimembered Evolution Strategy to Solve Constrained Optimization Problems. IEEE Trans on Evolutionary Computation,2005,9(1): 1-17 [10] Li Minqiang,Kou Jisong,Lin Dan. et al. Genetic Algorithm Theory and Application. Beijing,China: Science Press,2002(in Chinese) (李敏强,寇纪淞,林 丹,等.遗传算法的基本理论与应用.北京:科学出版社,2002) [11] Eberhartr R C,Shi Y. Guest Editorial: Special Issue on Particle Swarm Optimization. IEEE Trans on Evolutionary Computation,2004,8(3): 201-203 [12] Parsopoulos K E,Vrahatis M N. Initializing the Particle Swarm Optimizer Using the Nonlinear Simplex Method[EB/OL].[2012-08-01].http://www.math.upatras.gr/~kostasp/papers/wseas.pdf [13] Fan S K S,Zahara E. A Hybrid Simplex Search and Particle Swarm Optimization for Unconstrained Optimization. European Journal of Operational Research,2007,181(2): 527-548 [14] Wang Fang,Qiu Yuhui. Empirical Study of Hybrid Particle Swarm Optimizers with the Simplex Method Operator // Proc of the 5th International Conference on Intelligent Systems Design and Application. Wroclaw,Poland,2005: 308-313 [15] Wang Fang,Qiu Yuhui. Multimodal Function Optimizing by a New Hybrid Nonlinear Simplex Search and Particle Swarm Algorithm // Proc of the 16th European Conference on Machine Learning. Porto,Portugal,2005: 759-766 [16] Zhang Zongfei. Novel Improved Quantum Genetic Algorithm. Computer Engineering,2010,36(6): 181-183(in Chinese) (张宗飞.一种改进型量子遗传算法.计算机工程,2010,36(6): 181-183) [17] Hua Jie,Cui Duwu. Adaptive Niche Genetic Algorithm Based on Individual Optimization. Computer Engineering,2010,36(1): 194-196(in Chinese) (华 洁,崔杜武.基于个体优化的自适应小生境遗传算法.计算机工程,2010,36(1): 194-196) [18] Li Xiaolei,Shao Zhijiang,Qian Jixin. An Optimizing Method Based on Autonomous Animats: Fish-Swarm Algorithm. Systems 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.系统工程理论与实践,2002,22 (11): 32-38) [19] Zhou Yonghua,Mao Zongyuan. A New Search Algorithm for Global Optimization: Population Migration Algorithm (I). Journal of South China University of Technology: Natural Science Edition,2003,31(3): 1-5(in Chinese) (周永华,毛宗源. 一种新的全局优化搜索算法——人口迁移算法(Ⅰ).华南理工大学学报:自然科学版,2003,31(3): 1-5) [20] Rainer S,Price K. Differential Evolution—A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization,1997,11(4): 341-359 [21] Bogani C,Gasparo M G,Papini A. Generalizes Pattern Search Methods for a Class of Nonsmooth Optimization Problems with Structure. Journal of Computational and Applied Mathematics,2009,229(1): 283-293
2013, Vol. 26 
