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噪声环境下遗传算法的研究 被引量:2

Studies of genetic algorithm in noisy environment
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摘要 噪声环境下遗传算法的有效实现对于提高遗传算法实际应用价值具有非常重要的意义。文中对遗传算法领域的噪声环境以及噪声模型进行了分析和描述,着重从函数优化和模式定理分析了噪声环境对遗传算法的影响和主要原因,最后采用高斯噪声模拟噪声环境,对传统遗传算法和两种常用改进遗传算法进行了性能比较和分析。 Genetic algorithm realized effectively in noisy environment is great important for increasing its practical application value.This paper describes noisy environment,and enumerate some representative noise models which exhibites widely varying characteristics.Both the influence of GA in noisy environment and the reason are theoretically analyzed and simulated in computer by studying function optimal and schema theorem in noisy environment.Lastly,performances of SGA,NicheGA and PGA are compared and analyzed by putting them in Gaussiannoisy environment.
出处 《计算机工程与应用》 CSCD 北大核心 2009年第27期46-49,共4页 Computer Engineering and Applications
基金 国家自然科学基金No.60475002 江西省教育厅科学技术研究项目No.GJJ08209~~
关键词 噪声环境 噪声模型 遗传算法 函数优化 noisy environment noisy model genetic algorithm function optimization
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参考文献10

  • 1Arnold D V,Beyer H-G.A general noise model and its effects on evolution strategy performance[J].IEEE Transactions on Evolutionary Computation, 2006,10(4 ) : 380-391.
  • 2Fitzpatrick J M,Grenfenstette J J.Genetic algorithms in noisy environments[J].Machine Learning:Speical Issue on Genetic Algorithms, 1988(3 ) : 101-120.
  • 3Arnold D V,Beyer H-G.Local performance of the (1+1)-ES in a noisy environment[J].IEEE Trans Evol Comput, 2002,6( 1 ) : 30-41.
  • 4Arnold D V,Beyer H-G.Local performance of the (μ/μ1,λ)-ES in a noisy environment [M].San Francisco, CA: Morgan Kaufmann, 2001 : 127-141.
  • 5Arnold D V,Beyer H-G.Efficiency and self-adaptation of the (μ/μ1,λ)-ES in a noisy environment[M].Heidelberg,Germany:SpringerVerlag, 2000 : 39-48.
  • 6Arnold D V, Beyer H-G.A comparison of evolution strategies with other direct search methods in the presence of noise [J].Comput Optim, 2003,24 ( 1 ) : 135 - 159.
  • 7王晶,江弘,杨建军.噪声环境下的遗传算法[J].北京化工大学学报(自然科学版),2004,31(1):95-98. 被引量:2
  • 8郭彦.对柯西分布性质的进一步讨论[J].淮阴工学院学报,2005,14(5):8-9. 被引量:5
  • 9孔建新,尹家明.关于铅锌原矿Pb、Zn品位分布状况的研究[J].云南冶金,2007,36(6):54-59. 被引量:1
  • 10邱晓华,陈偕雄.非高斯噪声下系统参数M估计及其递推算法[J].科技通报,2007,23(6):867-872. 被引量:1

二级参考文献24

  • 1O.J.W.F.Kardaun,D.Salomé,W.Schaafsma,A.G.M.Steerneman,J.C.Willems,D.R.Cox,朱钰.对关于统计推断性质的十四个难以理解和有待澄清的问题的思考(中)[J].统计与信息论坛,2004,19(6):82-87. 被引量:1
  • 2[1]Hans-Georg B. Evolutionary algorithms in noisy environments: theoretical issues and guidelines for practice[J]. Computer Methods in Applied Mechanics and Engineering, 2000, 186: 239-267
  • 3[2]Fitzpatrick J M, Grefenstette J J. Genetic algorithms in noisy environments[M]. Machine Learning: Kluwer Academic Publishers, 1998,101-120
  • 4[3]Fogel D B, Ghozeil A. Scheme processing, proportional selection, and the misallocation of trials in genetic algorithms[J]. Information Sciences, 2000, 122: 93-119
  • 5[4]Rana S, Whitley L D, Cogswell R. Searching in the presence of noise[C]. ∥Proceedings of the Conference on Parallel Problem Solving from Nature, Heidelberg: Springer Press, 1996.199-207
  • 6[5]Fogel D B, Chellapilla K, Angeline P J. Inductive reasoning and bounded rationality reconsidered[J]. IEEE Trans On Evolutionary Computation, 1999, 3(2): 142-146
  • 7[6]Stagge P. Averaging efficiently in the presence of noise[C]. ∥Parallel Problem Solving from Nature-PPSN V 5th Int Conf Proc, Heidelberg: Springer Press, 1998, 188-197
  • 8[7]Then T W, Chong E K P. Genetic algorithm in noisy environment[C]. ∥IEEE International Symposium on Intelligent Control. USA, Columbus: Springer Press, 1994,225-230
  • 9李贤平 沈崇圣 陈子毅.概率论与数理统计[M].北京:复旦大学出版社,2003..
  • 10M. V. Menon, Ann. Math. Stat. [J]. 1992,33:1267-1271.

共引文献5

同被引文献15

  • 1郑金华.多目标遗传算法及其应用[M].北京:科学出版社,2007:61—69.
  • 2Arnold D V, Beyer H G.Efficiency and self-adaptation of the (u/uI,λ) - ES in a noisy environment[M].Heidelberg, Germany: Springer-Verlag, 2000 : 39-48.
  • 3Arnold D V,Beyer H G.Local performance of the (u/u, λ)-ES in a noisy environment[M].San Francisco, CA:Morgan Kaufmann,.2001:127-141.
  • 4Arnold D V,Beyer H G.Local performance of the (1+1)-ES in a noisy environment[J].IEEE Trans Evol Comput,2002,6(1): 30-41.
  • 5Arnold D V, Beyer H G.A comparison of evolution stratcgies with other direct search methods in the presence of noise[J]. Comput Optim, 2003,24 ( 1 ) : 135-159.
  • 6Yang S, Ong Y S, Jin Y.Evolutionary computation in dynamic and uncertain environments[M].Berlin:Springer,2007.
  • 7Luo B ,Zheng J H.A new methodology for searching robust pareto optimal solutions with MOEAs[C]//Proceeding of the 2008 IEEE Congress on Evolutionary Computation(IEEE CEC 2008), Hong Kong, China,2008 : 580-586.
  • 8Aizawa A N, Wah B W.Dynamic control of genetic algorithms in a noisy environment[C]//Proc Conf Genetic Algorithms, 1993: 48-55.
  • 9Aizawa A N, Wah B W.Scheduling of genetic algorithms in a noisy environment[J].Evol Comput, 1994,2(2) : 97-122.
  • 10Fitzpatrick J M, Grefenstette J I.Genetic algorithms in noisy environments[J].Mach Learn, 1988,3 : 101-120.

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