[1]李碧,林土胜.基于竞争协同进化的改进遗传算法[J].深圳大学学报理工版,2009,26(1):24-29.
 LI Bi and LIN Tu-sheng.Modified genetic algorithm based on competitive coevolution[J].Journal of Shenzhen University Science and Engineering,2009,26(1):24-29.
点击复制

基于竞争协同进化的改进遗传算法()
分享到:

《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第26卷
期数:
2009年1期
页码:
24-29
栏目:
电子与信息工程
出版日期:
2009-01-30

文章信息/Info

Title:
Modified genetic algorithm based on competitive coevolution
文章编号:
1000-2618(2009)01-0024-06
作者:
李碧12林土胜1
1)华南理工大学电子与信息学院,广州 510641
2)广东外语外贸大学信息科学技术学院,广州 510420
Author(s):
LI Bi12 and LIN Tu-sheng1
1)School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510641,P.R.China
2)School of Informatics,Guangdong University of Foreign Studies,Guangzhou 510420,P.R.China
关键词:
遗传算法早熟收敛竞争协同进化种群多样性函数优化
Keywords:
genetic algorithmpremature convergencecompetitivtioncoevolutionpopulation diversityfunction optimization
分类号:
TP 18;TP 301
文献标志码:
A
摘要:
针对标准遗传算法中的早熟收敛现象,提出一种基于竞争协同进化的改进遗传算法.该算法根据个体与对手竞争的表现来衡量个体的生存能力,生存能力由个体所击败对手的数量和优秀程度决定,个体在击败更多更优对手的努力中逐步进化.函数优化实验结果表明,该算法收敛速度快,且能有效保留种群多样性,与标准遗传算法及其他多种群遗传算法相比,能有效减轻早熟收敛现象.
Abstract:
To solve the problem of premature convergence in standard genetic algorithms (SGAs),this paper presents a modified genetic algorithm based on competitive coevolution (MGACC),in which an individual survival ability was assessed by its competitive performance relative to its opponents.The individual survival ability was determined by the number and characteristic of the opponents it defeats.All individuals were refined gradually during the endeavor to defeat more opponents or excellent opponents.Experimental results of benchmark function optimization show that MGACC converges rapidly,and alleviates the problem of premature convergence and maintains the population diversity more effectively,outperforms the competing genetic algorithms.

参考文献/References:


[1]Holland J H.自然系统和人工系统的自适应[M].剑桥(美国):麻省理工学院出版社,1992 (英文版).
[2]Goldberg D E.搜索、优化和机器学习中的遗传算法[M].新泽西:Addison Wesley出版公司,1989 (英文版).
[3]Plant W R,Schaefer G,Nakashima T.模拟足球赛中的遗传算法综述[C]//2008年度IEEE进化计算年会论文集.香港:IEEE出版社,2008:3898-3905(英文版).
[4]曹先彬,罗文坚,王煦法.基于生态种群竞争模型的协同进化[J].软件学报,2001,12(4):556-562.
[5]Salman A A,Mehrotra K,Mohan C K.自适应连锁交叉[J].进化计算,2000,8(3):341-370 (英文版).
[6]Zhang J,Chung H S H,Lo W L.基于聚类的自适应遗传算法自适应交叉和变异概率[J].IEEE进化计算汇刊,2007,11(3):326-335 (英文版).
[7]李碧,雍正正.基于多层竞争的高效并行遗传算法[J].电子学报,2002,30(12A):2161-2162.
[8]Ehrlich P R,Raven P H.蝴蝶与植物:协同进化研究[J].进化,1964,18:586-608 (英文版).
[9]Roughgarden J.竞争物种间的资源划分:一种协同进化方法[J].理论种群生态学,1976,9(3):388-424 (英文版).
[10]Hillis W D.协同进化的寄生物改善作为优化手段的模拟进化[J].物理学D,1990,42(1-3):228-234 (英文版).
[11]Rosin C D,R K Belew.面向竞争协同进化的新方法[J].进化计算,1997,5(1):1-29 (英文版).
[12]Cartlidge J,Bullock S.通过减小寄生物毒性来克服协同进化中的脱节现象[J].进化计算,2004,12(2):193-222 (英文版).
[13]De Jong K A.一类遗传自适应系统行为的分析:[D].密歇根:密歇根大学, 1975(英文版).
[14]Schaffer J D,Caruana R A,Eshelman L J.函数优化中影响遗传算法在线性能的参数控制[C]//第3届遗传算法会议论文集.洛斯拉图斯(美国):摩根考夫曼出版社,1989:51-60(英文版).
[15]董红斌,黄厚宽,印桂生,等.协同演化算法研究进展[J].计算机研究与发展,2008,45(3):454-463.
[16]Alba E,Tomassini M.并行性和进化算法[J].IEEE进化计算汇刊,2002,6(5):443-462 (英文版).

[1]Holland J H.Adaptation in Natural and Artificial Systems[M].Cambridge(USA):MIT Press,1975.
[2]Goldberg D E.Genetic Algorithms in Search,Optimization,and Machine Learning[M].New Jersey:Addison Wesley Publishing Company,1989.
[3]Plant W R,Schaefer G,Nakashima T.An overview of genetic algorithms in simulation soccer[C]//2008 IEEE Congress on Evolutionary Computation.Hong Kong:IEEE Press,2008:3898-3905.
[4]CAO Xian-bin,LUO Wen-jian,WANG Xi-fa.A co-evolution pattern based on ecological population competition model[J].Journal of Software,2001,12(4):556-562 (in Chinese).
[5]Salman A A,Mehrotra K,Mohan C K.Adaptive linkage crossover[J].Evolutionary Computation,2000,8(3):341-370.
[6]Zhang J,Chung H S H,Lo W L.Clustering-based adaptive crossover and mutation probabilities for genetic algorithms[J].IEEE Transactions on Evolutionary Computation,2007,11(3):326-335.
[7]LI Bi,YONG Zheng-zheng.A high-efficient parallel genetic algorithm based on multi-level competition[J].Acta Electronica Sinica,2002,30(12A):2161-2162 (in Chinese).
[8]Ehrlich P R,Raven P H.Butterflies and plants:a study in coevolution[J].Evolution,1964,18:586-608.
[9]Roughgarden J.Resource partitioning among competing species:a coevolutionary approach[J].Theoretical Population Biology,1976,9(3):388-424.
[10]Hillis W D.Co-evolving parasites improve simulated evolution as an optimization procedure[J].Physica D:Nonlinear Phenomena,1990,42(1-3):228-234.
[11]Rosin C D,Belew R K.New methods for competitive coevolution[J].Evolutionary Computation,1997,5(1):1-29.
[12]Cartlidge J,Bullock S.Combating coevolutionary disengagement by reducing parasite virulence[J].Evolutionary Computation,2002,12(2):193-222.
[13]Jong K A De.The analysis of the behavior of a class of genetic adaptive system[D].Michigan:University of Michigan,1975.
[14]Schaffer J D,Caruana R A,Eshelman L J.A study of control parameters affecting online performance of genetic algorithms for function optimization[C]//Proceedings of the 3rd International Conference on Genetic Algorithms.Los Altos(USA):Morgan Kaufmann Publish,1989:51-60.
[15]DONG Hong-bin,HUANG Hou-kuan,YIN Gui-sheng,et al.An overview of the research on coevolutionary algorithms[J].Journal of Computer Research and Development,2008,45(3):454-463 (in Chinese).
[16]Alba E,Tomassini M.Parallelism and evolutionary algorithms[J].IEEE Transactions on Evolutionary Computation,2002,6(5):443-462.

相似文献/References:

[1]姚锦宝,姚宝珍,尹智宏,等.基于双种群遗传算法的公交线路发车间隔优化[J].深圳大学学报理工版,2012,29(No.6(471-580)):559.[doi:10.3724/SP.J.1249.2012.06559]
 YAO Jin-bao,YAO Bao-zhen,YIN Zhi-hong,et al.A bus headway optimization model with dual-population genetic algorithm[J].Journal of Shenzhen University Science and Engineering,2012,29(1):559.[doi:10.3724/SP.J.1249.2012.06559]
[2]钟小品,徐刚.一种运动可靠的车辆主动悬挂线性控制器[J].深圳大学学报理工版,2013,30(No.2(111-220)):173.[doi:10.3724/SP.J.1249.2013.02173]
 Zhong Xiaopin and Xu Gang.A dynamic-reliable linear controller for active vehicle suspensions[J].Journal of Shenzhen University Science and Engineering,2013,30(1):173.[doi:10.3724/SP.J.1249.2013.02173]
[3]吴序一,伍晓宇.非量产模式下车间调度的改进遗传算法[J].深圳大学学报理工版,2006,23(3):272.
 WU Xu-yi and WU Xiao-yu.Improved genetic algorithm for job-shop scheduling[J].Journal of Shenzhen University Science and Engineering,2006,23(1):272.
[4]蔡良伟,胡世曦.基于相似性遗传算法及其在JSP中的应用[J].深圳大学学报理工版,2006,23(2):107.
 CAI Liang - wei and HU Shi - xi.A genetic algorithm based on similarity and its application on JSP[J].Journal of Shenzhen University Science and Engineering,2006,23(1):107.
[5]杨泽星,雍正正,俞敏,等.解决背包问题的改进遗传算法[J].深圳大学学报理工版,2006,23(2):128.
 YANG Ze-xing,YONG Zheng-zheng,YU Min,et al.Mutated genetic algorithm based-on advanced number solving KP[J].Journal of Shenzhen University Science and Engineering,2006,23(1):128.
[6]黄孔亮,雍正正.一种求解作业车间调度问题的协同进化算法[J].深圳大学学报理工版,2004,21(3):272.
 HUANG Kong-liang and YONG Zheng-zheng.A new coevolutionary genetic algorithm for job-shop scheduling problems[J].Journal of Shenzhen University Science and Engineering,2004,21(1):272.
[7]蔡良伟.基于距离测度的实数编码自适应遗传退火算法[J].深圳大学学报理工版,2004,21(4):291.
 CAI Liang-wei.Real-coded adaptive genetic annealing algorithm based on distance measurement[J].Journal of Shenzhen University Science and Engineering,2004,21(1):291.
[8]杨长雷,朱明程.用于进化硬件的遗传算法的选择策略初探[J].深圳大学学报理工版,2004,21(4):306.
 YANG Chang-lei and ZHU Ming-cheng.Studies on select strategy of genetic algorithm applied to evolvable hardware[J].Journal of Shenzhen University Science and Engineering,2004,21(1):306.
[9]杨雯,潘燕春,尹波腾,等.基于仿真的多级供应链补货策略优化[J].深圳大学学报理工版,2019,36(6):689.[doi:10.3724/SP.J.1249.2019.06689]
 YANG Wen,PAN Yanchun,YIN Boteng,et al.Simulation-based optimization of replenishment policy in multi-echelon supply chain[J].Journal of Shenzhen University Science and Engineering,2019,36(1):689.[doi:10.3724/SP.J.1249.2019.06689]
[10]邓连波,何渊,曾俊豪,等.需求可拆分下城轨关联的公交接驳线网优化[J].深圳大学学报理工版,2020,37(2):121.[doi:10.3724/SP.J.1249.2020.02121]
 DENG Lianbo,HE Yuan,ZENG Junhao,et al.Optimal design of feeder-bus network with split delivery[J].Journal of Shenzhen University Science and Engineering,2020,37(1):121.[doi:10.3724/SP.J.1249.2020.02121]

备注/Memo

备注/Memo:
收稿日期:2008-07-01;修回日期:2008-10-17
基金项目:国家自然科学基金资助项目(60673191);广东外语外贸大学团队创新资助项目(GW2006-TB-012);广东外语外贸大学青年资助项目(GW08Q02)
作者简介:李碧(1973-),男(汉族),湖南省涟源市人,广东外语外贸大学讲师、博士研究生.E-mail:libi@mail.gdufs.edu.cn
通讯作者:林土胜(1945-),男(汉族),华南理工大学教授、博士生导师.E-mail:eetshlin@scut.edu.cn
更新日期/Last Update: 2009-02-16