Abstract:A hybrid PSO algorithm based on memetic framework (HM-PSO) is proposed. It helps the particles which have certain leaning capacity accelerate convergence rate by Lamarckian Learning based local search strategy and helps the particles which fall into the local optimum escape from local optimum by Tabu search. HM-PSO avoids falling into the local optimum by enhancing the diversity of swarm with accelerating convergence rate. The experimental results show that the improved Lamarckian Learning strategy is effective and feasible and HM-PSO is an effective optimization algorithm with better global search performance.
[1] Moscato P.On Evolution,Search,Optimization,Genetic Algorithms and Martial Arts: Towards Memetic Algorithms.Technical Report,826.Pasadena,USA: California Institute of Technology,1989 [2] Liu Mandan.The Development of the Memetic Algorithm.Techniques of Automation and Applications,2007,26(11): 1-4,18 (in Chinese) (刘漫丹.文化基因算法(Memetic Algorithm)研究进展.自动化技术与应用,2007,26(11): 1-4,18) [3] Guo Xiuping,Yang Genke,Wu Zhiming.A Hybrid Adaptive Multi-Objective Memetic Algorithm.Control and Decision,2006,21(11): 1234-1238 (in Chinese) (郭秀萍,杨根科,吴智铭.一种混合自适应多目标Memetic算法.控制与决策,2006,21(11): 1234-1238) [4] Baos R,Gil C,Reca J,et al.A Memetic Algorithm Applied to the Design of Water Distribution Networks.Applied Soft Computing,2010,10(1): 261-266 [5] Chiam S C,Tan K C,Mamun A A.A Memetic Model of Evolutionary PSO for Computational Finance Applications.Expert Systems with Applications: An International Journal,2009,36(2): 3695-3711 [6] Ang J H,Tan K C,Mamun A A.An Evolutionary Memetic Algorithm for Rule Extraction.Expert Systems with Applications: An International Journal,2010,37(2): 1302-1315 [7] Ni Zhijian,Xing Hancheng,Zhang Zhizheng,et al.Survey of Particle Swarm Optimization Algorithm.Pattern Recognition and Artificial Intelligence,2007,20(3): 349-357 (in Chinese) (倪志剑,邢汉承,张志政,等.粒子群优化算法研究进展.模式识别与人工智能,2007,20(3): 349-357) [8] Rachid C,Patrick S.Tabu Search Applied to Global Optimization.European Journal of Operational Research.2000,123(2): 256-270 [9] Luan Zhibo,Huang Qitao,Jiang Hongzhou,et al.Mixed Application of Two Learning Mechanisms in Genetic Algorithm.Systems Engineering and Electronics,2009,31(8): 1985-1989 (in Chinese) (栾志博,黄其涛,姜洪洲,等.遗传算法中两种学习机制的混合应用.系统工程与电子技术,2009,31(8): 1985-1989) [10] Solis F J,Wets R T B.Minimization by Random Search Techniques.Mathematics of Operations Research,1981,6(1): 19-30 [11] Liang J J,Qin A K,Suganthan P N,et al.Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions.IEEE Trans on Evolutionary Computation,2006,10(3): 281-295 [12] Ji Zhen,Zhou Jiarui,Liao Huilian,et al.A Novel Intelligent Single Particle Optimizer.Chinese Journal of Computers,2010,33 (3): 556-561 (in Chinese) (纪 震,周家锐,廖惠连,等.智能单粒子优化算法.计算机学报,2010,33(3): 556-561)