基于种群概率模型的优化技术：从算法到应用（英文版）

图书标准信息

• 作者 姜群 著
• 出版社 上海交通大学出版社
• 出版时间 2010-04
• 版次 1
• ISBN 9787313063694
• 定价 48.00元
• 装帧 平装
• 开本 16开
• 纸张 胶版纸
• 页数 156页
• 字数 191千字
• 正文语种 英语

【内容简介】

《基于种群概率模型的优化技术：从算法到应用（英文版）》较系统地讨论了遗传算法和分布估计算法的基本理论，并在二进制搜寻空间实验性地比较了几种分布估算法。在此基础上深入地论述了构建一类新的分布估计算法的思路和实现方法，最后介绍了分布估计算法在计算机科学、资源管理等领域的一些成功应用实例及分布估计算法的几种有效改进方法。

【目录】

Chapter1FundamentalsandLiterature
1.1OptimizationProblems
1.2CanonicalGeneticAlgorithm
1.3IndividualRepresentations
1.4Mutation
1.5Recombination
1.6PopulationModels
1.7ParentSelection
1.8SurvivorSelection
1.9Summary

Chapter2TheProbabilisticModel-buildingGeneticAlgorithms
2.1Introduction
2.2ASimpleOptimizationExample
2.3DifferentEDAApproaches
2.4OptimizationinContinuousDomainswithEDAs
2.5Summary

Chapter3AnEmpiricalComparisonofEDAsinBinarySearchSpaces
3.1Introduction
3.2Experiments
3.3TestFunctionsfortheConvergenceReliability
3.4ExperimentalResults
3.5Summary

Chapter4DevelopmentofaNewTypeofEDAsBasedonPrincipleofMaximumEntropy
4.1Introduction
4.2EntropyandSchemata
4.3TheIdeaoftheProposedAlgorithms
4.4HowCantheEstimatedDistributionbeComputedandSampled?
4.5NewAlgorithms
4.6EmpiricalResults
4.7Summary

Chapter5ApplyingContinuousEDAstoOptimizationProblems
5.1Introduction
5.2DescriptionoftheOptimizationProblems
5.3EDAstoTest
5.4ExperimentalDescription
5.5Summary

Chapter6OptimizingCurriculumSchedulingProblemUsingEDA
6.1Introduction
6.2OptimizationProblemofCurriculumScheduling
6.3Methodology
6.4ExperimentalResults
6.5Summary

Chapter7RecognizingHumanBrainImagesUsingEDAs
7.1Introduction
7.2GraphMatchingProblem
7.3RepresentingaMatchingasaPermutation
7.4ApplyEDAstoObtainaPermutationthatSymbolizestheSolution
7.5ObtainingaPermutationwithContinuousEDAs
7.6ExperimentalResults
7.7Summary

Chapter8OptimizingDynamicPricingProblemwithEDAsandGA
8.1Introduction
8.2DynamicPricingforResourceManagement
8.3ModelingDynamicPricing
8.4AnEAApproachestoDynamicPricing
8.5ExperimentsandResults
8.6Summary

Chapter9ImprovementTechniquesofEDAs
9.1Introduction
9.2TradeoffsareExploitedbyEfficiency-ImprovementTechniques
9.3EvaluationRelaxation:DesigningAdaptiveEndogenousSurrogates
9.4TimeContinuation:MutationinEDAs
9.5Summary