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基于文化差分算法的无约束优化问题研究 被引量：1

Research on Solving Unconstrained Optimization Based on Cultural-Differential Algorithm
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摘要 无约束优化问题是一个较古老的数学问题,随着智能计算科学的发展,解决此类优化问题,除了使用经典数学方法外,还可以使用智能化方法进行寻优。本文使用经典文化算法双层进化结构,将差分进化算法引入信度空间的更新操作,实现差分进化算法在进化过程中形势知识更新,保证了种群合理的进化方向,从而引导种群空间中个体进行有效进化,使得寻优能力有所提高,并选用6个基准函数对改进前后的算法进行测试,实验表明优化性能得到了提高。 Unconstrained optimization is an ancient mathematics issue,due to the development of the intelligent computing science,there are many of techniques that can cope with such problems as well,besides classic mathematics＇ method.This paper takes advantage of the cultural algorithm＇s double-layers architecture and embeds the differential evolution in updating operation of the knowledge space to achieve situationable knowledge updating by differential evolution during evolution of the whole architecture,then population space makes use of all these information to assure correct evolution direction and to fulfill individual evolution efficiently in order to improve the algorithm＇s performance.This paper selects 6 benchmark functions to test the classic algorithm and the improved algorithm.The results demonstrate that the later improves the performance.
作者 周小文 蒋泽军
机构地区 西北工业大学计算机学院
出处 《计算机与现代化》 2013年第2期48-51,共4页 Computer and Modernization
关键词 无约束优化 文化算法 差分进化 unconstrained optimization cultural algorithm differential evolution
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献14

  • 1Reynolds R G. An introduction to cultural algorithms[C]//Proceedings of the Third Annual Conference on EvolutionaryProgramming. 1994:131-139.
  • 2Nguyen T T, Yao X. Hybridizing cultural algorithms andlocal search [ C ] //Proceedings of the 7 th International Con-ference on Intelligent Data Engineering and AutomatedLearning. 2006:586-594.
  • 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,2007,33(10):1115-1120. 被引量：40
  • 4Reynolds R G, Peng B. Knowledge learning and socialswarms in culture algorithms[ J]. Journal o? MathematicalSociology, 2005,29(2):115-132.
  • 5Gao Fang, Cui Gang, Liu Hongwei. Integration of geneticalgorithm and cultural algorithms for constrained optimiza-tion[ C]// Proceedings of the 13th International Conferenceon Neural Information Processing. 2006,Part III; 817-825.
  • 6Ricardo Landa Becerra, Carlos A Coello Coello. A culturalalgorithm with differential evolution to solve constrained op-timization problems [ C ] //Lecture Notes in Computer Sci-ence, 2004,3315:881-890.
  • 7Reynolds R G, Zhu S. Knowledge-based function optimiza-tion using fuzzy cultural algorithms with evolutionary programming[J]. IEEE Transactions on Systems, Man, andCybemetics-Part B: Cybernetics, 2001,31 (1) :1-18.
  • 8Vesterstrom J, Thomsen R. A comparative study of differ-ential evolution, particle swarm optimization t and evolu-tionary algorithms on numerical benchmark problems [ C ] //Proceedings of Congress on Evolutionary Computation(CEC2004). 2004:1980-1987.
  • 9Stom R. System design by constraint adaptation and differ-ential evolution [ J ]. IEEE Transactions on EvolutionaryComputation,1999,3( 1) :22-34.
  • 10Iacoban R, Reynolds R G, Brewster J. Cultural swarms:Modeling the impact of culture on social interaction andproblem solving [ C ] //Proceedings of the 2003 IEEE SwarmIntelligence Symposium. 2003:205-211.

二级参考文献17

  • 1贺益君,陈德钊.连续约束蚁群优化算法的构建及其在丁烯烷化过程中的应用[J].化工学报,2005,56(9):1708-1713. 被引量：12
  • 2Robert R G.An introduction to cultural algorithms.In:Proceedings of the 3rd Annual Conference Evolution Programming.Singapore:World Scientific Publishing,1994.131-136
  • 3Renfrew A C.Dynamic Modeling in Archaeology:What,When,and Where? Dynamical Modeling and the Study of Chang in Archaeology.Edinburgh Scotland:Edinburgh University Press,1994
  • 4Trung T N,Xin Y.Hybridizing cultural algorithms and local search.Lecture Notes in Comptuer Science.Springer,2006,4224:586-594
  • 5Reynolds R G,Peng B.Knowledge learning and social swarms in culture algorithms.The Journal of Mathematic Sociology,2005,29(2):115-132
  • 6Ricardo L B,Carlos A,Coello C.A cultural algorithm with differential evolution to solve constrained optimization problems.Lecture Notes in Compture Science.Springer,2004,3315:881-890
  • 7Gao F,Cui G,Liu H W.Integration of genetic algorithm and cultural algorithms for constrained optimization.Lecture Notes in Comptuer Science.Springer,2006,4234:817-825
  • 8Yuan X H,Yuan Y B.Application of cultural algorithm to generation scheduling of hydrothermal systems.Energy Conversion and Management,2006,47:2192-2201
  • 9Reynolds R G,Saleem S.Culture algorithmsin dynamic environments.In:Proceedings of Congress on Evolutionary Computation.SanDiego,California,2000.2:1513-1520
  • 10Coello C A,Becerra R I.Evolutionary multiobjective optimization using a cultural algorithm.In:Proceedings of 2003 IEEE Swarm Intelligence Symposium.Indianapolis,Indiana,IEEE Service Center,2003.6-13

共引文献39

同被引文献19

  • 1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,2007,33(10):1115-1120. 被引量：40
  • 2XIDONG J, REYNOLDS R G. Using knowledge-based evolutionary computation to solve nonlinear con- straint optimization problem: a cultural algorithm approach [C]//IEEE Congress on Evolutionary Com- putation, 1999: 1672-1678.
  • 3MOLINA D, LOZANO M, SANCHEZ t 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.
  • 4ALl M, REYNOLDS R. The emergence of cultural hi- erarchical social networks in complex environments [J]. Artificial Intelligence: Methodology, Systems and Applications, 2012: 69-78.
  • 5RAEESI M N, KOBT! Z. A multiagent system to solve JSSP using a multi-population cultural algorithm [C]//Advances in Artificial Intelligence, 2012: 362- 367.
  • 6OCHOA A, GARCIA Y, YANEZ J, TEYMANOGLU Y. Using cultural algorithms to improve intelligent lo- gistics [C]//Hybrid Artificial Intelligence Systems, 2010: 127-134.
  • 7CHANJIN C. Knowledge-based approaches to self- adaptation in cultural algorithms [D]. Detroit, Miehi- gan: Waynestate University, 1997.
  • 8SALEEM S M. Knowledge-based solution to dynamic optimization problems using cultural algorithms [D]. USA: Wayne State University, 2001.
  • 9BEEERA R L, COELLO C A. Optimization with con- straints using a cultured differential evolution ap- proach [C]//Proceedings of the 2005 conference on Genetic and Evolutionary Computation, 2005: 27- 34.
  • 10ROBERT G, REYNOLDS R, PENG B, ALOMARI R S. Cultural evolution of ensemble learning for problem solving [C]//IEEE Congress on Evolutionary Com- putation, 2006: 1119-1126.

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计算机与现代化
2013年 第2期

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