摘要
针对以往文化算法种群空间没有地域的概念,信念空间缺少文化的进化机制,以及求解优化问题时寻优精度不高且易陷入局部最优等缺陷,提出一种新的基于元胞空间结构的文化算法.将元胞空间网格分别嵌入文化算法计算框架中的种群空间和信念空间以模拟文化算法的双层进化体系;对于种群空间,将进化个体分布于下层元胞网格,并对网格进行地域划分,使每个地域内的个体均以差分进化算子独立进化;对于信念空间,将进化信息放入与种群空间地域对应的上层元胞网格当中,利用文化的扩散机制实现文化的进化.实验结果表明,该算法具有收敛精度高以及全局搜索能力强等优点,在处理高维复杂优化问题时同样具有优势.
To solve the problems in the cultural algorithm has a number of problems,for example,lack of a region concept in the population space,lack of cultural evolution in the belief space,and defects such as low accuracy and being easy to fall into a local optimum.This paper proposes a new cultural algorithm based on cellulaj space structure.It can simulate a double-layer evolutionary system of culture algorithm by embedding a cellular space grid structure in the framework of computing population space and belief space.For the population space,the evolutionary individuals are distributed in the lower cellular space grid.The grid is divided into many areas so that individuals in each area evolve independently by using differential evolution algorithm.For the belief space,the evolution information is put into the upper grid corresponding to the population space,and the evolution of culture is realized using a diffusion mechanism of culture.Experimental results show that the algorithm is effective in convergence accuracy and global search capability,and has advantages in dealing with complex high-dimensional optimization problems.
引文
[1]Xidong J,Reynolds R G.Using knowledge-based evolutionary computation to solve nonlinear constraint optimization problem:a cultural algorithm approach[C]//IEEE Congress on Evolutionary Computation,1999:1672-1678.
[2]吴亚丽,徐丽青.一种基于粒子群算法的改进多目标文化算法[J].控制与决策,2012,8:1127-1132.Wu Yali,Xu Liqing.An improved multi-objective cultural algorithm based on particle swarm optimization[J].Control and Decision,2012,8:1127-1132.(in Chinese)
[3]黄海燕,顾幸生,刘漫丹.求解约束优化问题的文化算法研究[J].自动化学报,2007,10:1115-1120.Huang Haiyan,Gu Xingsheng,LIu Mandan.Research on cultural algorithm for solving nonlinear constrained optimization[J].Acta Automatica Sinica,2007,10:1115-1120.(in Chinese)
[4]Molina D,Lozano M,Sanchez A M,Herrera F.Memetic algorithms based on local search chains for large scale continuous optimization problems:MA-SSW-Chains[J].Soft Computing,2011,15(11):2201-2220.
[5]Ali M,Reynolds R.The emergence of cultural hierarchical social networks in complex environments[J].Artificial Intelligence:Methodology,Systems and Applications,2012:69-78.
[6]柴玉梅,陈阳,苏金,明奇.基于人工鱼的全局优化文化算法[J].郑州大学学报:工学版,2010,31(5):106—110.Chai Yumei,Chen Yang,Su Jin,Ming Qi.Cultural algorithm based on artificial fish for global optimization[J].Journal of Zhengzhou University:Engineering science,2010,31(5):106-110.(in Chinese)
[7]Raeesi M N,Kobti Z.A multiagent system to solve JSSP using a multi-population cultural algorithm[C]//Advances in Artificial Intelligence,2012:362-367.
[8]Ochoa A,Garcia Y,Yanez J,Teymanoglu Y.Using cultural algorithms to improve intelligent logistics[C]//Hybrid Artificial Intelligence Systems,2010:127-134.
[9]Chanjin C.Knowledge-based approaches to selfadaptation in cultural algorithms[D].Detroit,Michigan:Waynestate University,1997.
[10]Saleem S M.Knowledge-based solution to dynamic optimization problems using cultural algorithms[D].USA:Wayne State University,2001.
[11]陈思华,陶长琪.一种新的文化算法框架下知识融合策略[J].小型微型计算机系统,2009,30(10):2030-2033.Chen Sihua,Tao Changqi.New knowledge integration strategy based on culture algorithm framework[J].Journal of Chinese Computer Systems,2009,30(8):2030-2033.(in Chinese)
[12]Beeera R L,Coello C A.Optimization with constraints using a cultured differential evolution approach[C]//Proceedings of the 2005 conference on Genetic and Evolutionary Computation,2005:27-34.
[13]Robert G,Reynolds R,Peng B,Alomari R S.Cultural evolution of ensemble learning for problem solving[C]//IEEE Congress on Evolutionary Computation,2006:1119-1126.
[14]艾景波.文化粒子群优化算法及其在布局设计中的应用研究[D].大连:大连理工大学,2005.
[15]陈吴,黎明,陈曦.处理动态优化问题的捕食元胞遗传算法[J].控制与决策,2012(6):827—832.Chen Hao,Li Ming,Chen Xi.Predator-prey cellular genetic algorithm for solving dynamic optimization problems[J].Control and Decision,2012(6):827-832.(in Chinese)
[16]鲁宇明,黎明,李凌,杨红雨.基于个体差异移民的改进元胞遗传算法[J].系统工程与电子技术,2011(3):690-693.LU Yuming,LI Ming,LI Ling,Yang Hongyu.Improved cellular genetic algorithm based on migration of different individuals[J],Systems Engineering and Electronics,2011(3):690-693.(in Chinese)
[1 7]陈吴,黎明,江泽涛,储珺.处理动态优化问题的演化元胞遗传算法[J].系统工程与电子技术,2013,35(5):1115—1121.Chen Hao,LI Ming,Jiang Zetao,Chu Jun.Evolution cellular genetic algorithm for solving dynamic optimization problem[J].Systems Engineering and Electronics,2013,35(5):1115-1121.(in Chinese)
[18]拓守恒,陶维天.一种求解高维多模态复杂问题的差分文化算法[J].计算机工程与科学,2013,1:142—148Tuo Shouheng,Tao Weitian.A novel differential evolution based cultural algorithm for solving highdimensional multimodal optimization problems[J].Computer Engineering and Science,2013,1:142-148.(in Chinese)
[19]周小文,蒋泽军.基于文化差分算法的无约束优化问题研究[J].计算机与现代化,2013,2:48—51.Zhou Xiaowen,Jiang Zejun.Research on solving unconstrained optimization based on culturaldifferential algorithm[J].Computer and Modernization,2013,2:48-51.(in Chinese)
[20]鲁宇明,黎明,李凌.一种具有演化规则的元胞遗传算法[J].电子学报,2010,38(7):1603-1607.LU Yuming,LI Ming,LI Ling.The cellular genetic algorithm with evolutionary rule[J].Acta Electronica Sinica,2010,38(7):1603-1607.(in Chinese)
[21]李军华,黎明.噪声环境下多模态函数优化的遗传算法[J].电子学报,2012(2):327-330.LI Junhua,LI Ming.Genetic algorithm for multimodal function optimization in noisy environments[J].Acta Electronica Sinica,2012(2):327-330.(in Chinese)
