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基于非劣排序的多目标优化免疫遗传算法 被引量：1

Immune Genetic Multi-objective Optimization Algorithms Based on Non-dominated Sorting
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摘要 提出一种基于非劣排序的多目标优化免疫遗传算法。算法基于非劣排序对种群进行分类来评价个体的价值,在选择操作中引入个体浓度保持种群多样性。采用免疫克隆操作为产生新种群和算法实现全局搜索提供了基础,采用遗传种群与父代群体锦标赛竞争的方式保留最优解。仿真实验结果表明:算法在收敛性和分布性方面要优于NSGA-II算法。 The paper represented An Immune Genetic Multi-objective Optknization Algorithms based on non-dominated sort-ing. Based 9n Immune Genetic Algorithm, the algorithm evaluated individuals fitting values in current population using Paretosorting method, used concentration as selecdon criteria to keep population good diversity. This algorithm also used the immuneclone operationn to generate new population and implemented global searching process. Then a tournament selection betweenparent and genetie population was adopted to obtain optimal solutions. The simulation results showed that the algorithm wasbetter than NSGA-II algorithm in convergence and distribution capabilities.
作者 郭志刚 邹书蓉
机构地区 成都信息工程学院计算机学院
出处 《成都信息工程学院学报》 2012年第2期136-141,共6页 Journal of Chengdu University of Information Technology
关键词 计算机应用 智能工程 非劣排序 多目标 免疫遗传算法 浓度 免疫克隆 computer application intelligent engineering non-dominated sorting multi-object immune genetic algo-rithm concentration immune clone
分类号 O224 [理学—运筹学与控制论]
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参考文献16

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同被引文献11

  • 1Gen M,Li Y Z. Spanrdng tree-based genetic algorithm for bicrite- ria fixed charge transportation problem [ C ]//Proceedings of the 1999 Congress on Evolutionary Computation. Washington, DC: IEEE Press, 1999:2265 - 2271.
  • 2Gen Mitsuo, Cheng Runwei. Genetic algorithms and engineering optimization[ M] .New York:John Wiley&sons,Inc., 1999.
  • 3Das Indraned. A closer look at drawbacks of minimizing weighted sums of objectives for pareto set generation in muhicriteria optimi- zation problems [ J ]. Structural Optimization, 1997, 14 ( 1 ) : 63 - 69.
  • 4Zhang Hongwei, Yang Zhenyu, Zou Shurong. Multi-objective su- pervised clustering CA and megathermal climate forecast [ C ] // IEEE 2011 International Conference on Management and Service Schence. Wuhan: IEEE Press, 2011 : 20 - 23.
  • 5Zhang Hongwei, Cul Xiaoke,Zou Shurong. Multi objective trans- portation optimization based on fmcica [ C ]//The 2 nd IEEE Inter- national Conference on Information Management and Engineer- ing. Chengdu: IEEE Press,2010:426 - 430.
  • 6Kotsiantis S B, Pintelas P E. Logitboost of simple bayesian clas- sifier [ J].Informatica, 2005,29: 53 - 59.
  • 7Todorovski L, Dzeroski S. Experiments in meta-level learning with ILP [ C ]//Third European Conference, PKDD ' 99. Pragve : Springer Berlin Herdelberg, 1999:98- 106.
  • 8Petri K, Jussi L, Petri M, et al. Unsupervised bayesian visualiza- tion of high-dimensional data[ C]//Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Disctrtery and Data Mining. Boston:ACM Press,2000:325- 329.
  • 9孙吉贵,刘杰,赵连宇.聚类算法研究[J].软件学报,2008(1):48-61. 被引量：1070
  • 10黄晓滨,邹书蓉,张洪伟.免疫遗传算法及其在VRP中的应用[J].成都信息工程学院学报,2008,23(6):637-641. 被引量：5

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成都信息工程学院学报
2012年 第2期

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