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运筹学导论

作者: 塔哈（Hamdy A.Taha）著

出版社: 人民邮电出版社

出版时间: 2007-07

版次: 1

ISBN: 9787115160652

定价: 59.00

装帧: 平装

开本: 其他

纸张: 其他

页数: 994页

正文语种: 英语

丛书: 图灵原版数学·统计学系列

分类: 自然科学

31人买过

　　《运筹学导论：高级篇（英文版·第8版）》是运筹学方面的经典著作之一，为全球众多高校采用。高级篇共12章，内容包括高级线性规划、概率论基础复习、概率库存模型、模拟模型、马尔可夫链、经典最优化理论、非线性规划算法、网络和线性规划算法进阶、预测模型、概率动态规划、马尔可夫决策过程、案例分析等，并附有统计表、部分习题的解答、向量和矩阵复习及案例研究。
　　《运筹学导论：高级篇（英文版·第8版）》可供经管类专业和数学专业研究生以及MBA作为教材或者参考书，也可供相关研究人员参考。　　HamdyA.Taha美国阿肯色大学荣休教授，世界知名运筹学家，曾在全球各地教和担任顾问，同时拥有非常丰富的教学研究和实践经验。他在ManagementScience和OperationsResearch等世界顶级学术刊物上发表了大量论文。 Chapter13　AdvancedLinearProgramming
13.1　SimplexMethodFundamentals
13.1.1　FromExtremePointstoBasicSolutions
13.1.2　GeneralizedSimplexTableauinMatrixForm
13.2　RevisedSimplexMethod
13.2.1　DevelopmentoftheOptimalityandFeasibilityConditions
13.2.2　RevisedSimplexAlgorithm
13.3　Bounded-VariablesAlgorithm
13.4　Duality
13.4.1　MatrixDefinitionoftheDualProblem
13.4.2　OptimalDualSolution
13.5　ParametricLinearProgramming
13.5.1　ParametricChangesinC
13.5.2　ParametricChangesinb
References

Chapter14　ReviewofBasicProbability
14.1　LawsofProbability
14.1.1　AdditionLawofProbability
14.1.2　ConditionalLawofProbability
14.2　RandomVariablesandProbabilityDistributions
14.3　ExpectationofaRandomVariable
14.3.1　MeanandVariance(StandardDeviation)ofaRandomVariable
14.3.2　MeanandVarianceofJointRandomVariables
14.4　FourCommonProbabilityDistributions
14.4.1　BinomialDistribution
14.4.2　PoissonDistribution
14.4.3　NegativeExponentialDistribution
14.4.4　NormalDistribution
14.5　EmpiricalDistributions
References

Chapter15　ProbabilisticInventoryModels
15.1　ContinuousReviewModels
15.1.1　“Probabilitized”EOQModel
15.1.2　ProbabilisticEOQModel
15.2　Single-PeriodModels
15.2.1　No-SetupModel(NewsvendorModel)
15.2.2　SetupModel(s-SPolicy)
15.3　MultiperiodModel
References

Chapter16　SimulationModeling
16.1　MonteCarloSimulation
16.2　TypesofSimulation
16.3　ElementsofDiscrete-EventSimulation
16.3.1　GenericDefinitionofEvents
16.3.2　SamplingfromProbabilityDistributions
16.4　GenerationofRandomNumbers
16.5　MechanicsofDiscreteSimulation
16.5.1　ManualSimulationofaSingle-ServerModel
16.5.2　Spreadsheet-BasedSimulationoftheSingle-ServerModel
16.6　MethodsforGatheringStatisticalObservations
16.6.1　SubintervalMethod
16.6.2　ReplicationMethod
16.6.3　Regenerative(Cycle)Method
16.7　SimulationLanguages
References

Chapter17　MarkovChains
17.1　DefinitionofaMarkovChain
17.2　Absoluteandn-StepTransitionProbabilities
17.3　ClassificationoftheStatesinaMarkovChain
17.4　Steady-StateProbabilitiesandMeanReturnTimesofErgodicChains
17.5　FirstPassageTime
17.6　AnalysisofAbsorbingStates
References

Chapter18　ClassicalOptimizationTheory
18.1　UnconstrainedProblems
18.1.1　NecessaryandSufficientConditions
18.1.2　TheNewton-RaphsonMethod
18.2　ConstrainedProblems
18.2.1　EqualityConstraints
18.2.2　InequalityConstraints-Karush-Kuhn-Tucker(KKT)Conditions
References

Chapter19　NonlinearProgrammingAlgorivthms
19.1　UnconstrainedAlgorithms
19.1.1　DirectSearchMethod
19.1.2　GradientMethod
19.2　ConstrainedAlgorithms
19.2.1　SeparableProgramming
19.2.2　QuadraticProgramming
19.2.3　Chance-ConstrainedProgramming
19.2.4　LinearCombinationsMethod
References

Chapter20　AdditionalNetworkandLPAlgorithms
20.1　Minimum-CostCapacitatedFlowProblem
20.1.1　NetworkRepresentation
20.1.2　LinearProgrammingFormulation
20.1.3　CapacitatedNetworkSimplexAlgorithm
20.2　DecompositionAlgorithm
20.3　KarmarkarInterior-PointMethod
20.3.1　BasicIdeaoftheInterior-PointAlgorithm
20.3.2　Interior-PointAlgorithm
References

Chapter21　ForecastingModels
21.1　MovingAverageTechnique
21.2　ExponentialSmoothing
21.3　Regression
References

Chapter22　ProbabilisticDynamicProgramming
22.1　AGameofChance
22.2　InvestmentProblem
22.3　MaximizationoftheEventofAchievingaGoal
References

Chapter23　MarkovianDecisionProcess
23.1　ScopeoftheMarkovianDecisionProblem
23.2　Finite-StageDynamicProgrammingModel
23.3　Infinite-StageModel
23.3.1　ExhaustiveEnumerationMethod
23.3.2　PolicyIterationMethodWithoutDiscounting
23.3.3　PolicyIterationMethodwithDiscounting
23.4　LinearProgrammingSolution
References

Chapter24　CaseAnalysis
Case1：AirlineFuelAllocationUsingOptimumTankering
Case2：OptimizationofHeartValvesProduction
Case3：SchedulingAppointmentsatAustralianTouristCommissionTradeEvents
Case4：SavingFederalTravelDollars
Case5：OptimalShipRoutingandPersonnelAssignmentforNavalRecruitmentinThailand
Case6：AllocationofOperatingRoomTimeinMountSinaiHospital
Case7：OptimizingTrailerPayloadsatPFGBuildingGlass
Case8：OptimizationofCrosscuttingandLogAllocationatWeyerhaeuser
Case9：LayoutPlanningforaComputerIntegratedManufacturing(CIM)Facility　Case10：BookingLimitsinHotelReservations
Case11：CaseysProblem：InterpretingandEvaluatingaNewTest
Case12：OrderingGolfersontheFinalDayofRyderCupMatches
Case13：InventoryDecisionsinDellsSupplyChain
Case14：AnalysisofanInternalTransportSysteminaManufacturingPlant
Case15：TelephoneSalesManpowerPlanningatQantasAirways
AppendixB　StatisticalTables
AppendixC　PartialSolutionstoAnswersProblems
AppendixD　ReviewofVectorsandMatrices
D.1　Vectors
D.1.1　DefinitionofaVector
D.1.2　Addition(Subtraction)ofVectors
D.1.3　MultiplicationofVectorsbyScalars
D.1.4　LinearlyIndependentVectors
D.2　Matrices
D.2.1　DefinitionofaMatrix
D.2.2　TypesofMatrices
D.2.3　MatrixArithmeticOperations
D.2.4　DeterminantofaSquareMatrix
D.2.5　NonsingularMatrix
D.2.6　InverseofaNonsingularMatrix
D.2.7　MethodsofComputingtheInverseofMatrix
D.2.8　MatrixManipulationsUsingExcel
D.3　QuadraticForms
D.4　ConvexandConcaveFunctions
Problems
SelectedReferences
AppendixECaseStudies
内容简介:
　　《运筹学导论：高级篇（英文版·第8版）》是运筹学方面的经典著作之一，为全球众多高校采用。高级篇共12章，内容包括高级线性规划、概率论基础复习、概率库存模型、模拟模型、马尔可夫链、经典最优化理论、非线性规划算法、网络和线性规划算法进阶、预测模型、概率动态规划、马尔可夫决策过程、案例分析等，并附有统计表、部分习题的解答、向量和矩阵复习及案例研究。
　　《运筹学导论：高级篇（英文版·第8版）》可供经管类专业和数学专业研究生以及MBA作为教材或者参考书，也可供相关研究人员参考。
作者简介:
　　HamdyA.Taha美国阿肯色大学荣休教授，世界知名运筹学家，曾在全球各地教和担任顾问，同时拥有非常丰富的教学研究和实践经验。他在ManagementScience和OperationsResearch等世界顶级学术刊物上发表了大量论文。
目录:
Chapter13　AdvancedLinearProgramming
13.1　SimplexMethodFundamentals
13.1.1　FromExtremePointstoBasicSolutions
13.1.2　GeneralizedSimplexTableauinMatrixForm
13.2　RevisedSimplexMethod
13.2.1　DevelopmentoftheOptimalityandFeasibilityConditions
13.2.2　RevisedSimplexAlgorithm
13.3　Bounded-VariablesAlgorithm
13.4　Duality
13.4.1　MatrixDefinitionoftheDualProblem
13.4.2　OptimalDualSolution
13.5　ParametricLinearProgramming
13.5.1　ParametricChangesinC
13.5.2　ParametricChangesinb
References

Chapter14　ReviewofBasicProbability
14.1　LawsofProbability
14.1.1　AdditionLawofProbability
14.1.2　ConditionalLawofProbability
14.2　RandomVariablesandProbabilityDistributions
14.3　ExpectationofaRandomVariable
14.3.1　MeanandVariance(StandardDeviation)ofaRandomVariable
14.3.2　MeanandVarianceofJointRandomVariables
14.4　FourCommonProbabilityDistributions
14.4.1　BinomialDistribution
14.4.2　PoissonDistribution
14.4.3　NegativeExponentialDistribution
14.4.4　NormalDistribution
14.5　EmpiricalDistributions
References

Chapter15　ProbabilisticInventoryModels
15.1　ContinuousReviewModels
15.1.1　“Probabilitized”EOQModel
15.1.2　ProbabilisticEOQModel
15.2　Single-PeriodModels
15.2.1　No-SetupModel(NewsvendorModel)
15.2.2　SetupModel(s-SPolicy)
15.3　MultiperiodModel
References

Chapter16　SimulationModeling
16.1　MonteCarloSimulation
16.2　TypesofSimulation
16.3　ElementsofDiscrete-EventSimulation
16.3.1　GenericDefinitionofEvents
16.3.2　SamplingfromProbabilityDistributions
16.4　GenerationofRandomNumbers
16.5　MechanicsofDiscreteSimulation
16.5.1　ManualSimulationofaSingle-ServerModel
16.5.2　Spreadsheet-BasedSimulationoftheSingle-ServerModel
16.6　MethodsforGatheringStatisticalObservations
16.6.1　SubintervalMethod
16.6.2　ReplicationMethod
16.6.3　Regenerative(Cycle)Method
16.7　SimulationLanguages
References

Chapter17　MarkovChains
17.1　DefinitionofaMarkovChain
17.2　Absoluteandn-StepTransitionProbabilities
17.3　ClassificationoftheStatesinaMarkovChain
17.4　Steady-StateProbabilitiesandMeanReturnTimesofErgodicChains
17.5　FirstPassageTime
17.6　AnalysisofAbsorbingStates
References

Chapter18　ClassicalOptimizationTheory
18.1　UnconstrainedProblems
18.1.1　NecessaryandSufficientConditions
18.1.2　TheNewton-RaphsonMethod
18.2　ConstrainedProblems
18.2.1　EqualityConstraints
18.2.2　InequalityConstraints-Karush-Kuhn-Tucker(KKT)Conditions
References

Chapter19　NonlinearProgrammingAlgorivthms
19.1　UnconstrainedAlgorithms
19.1.1　DirectSearchMethod
19.1.2　GradientMethod
19.2　ConstrainedAlgorithms
19.2.1　SeparableProgramming
19.2.2　QuadraticProgramming
19.2.3　Chance-ConstrainedProgramming
19.2.4　LinearCombinationsMethod
References

Chapter20　AdditionalNetworkandLPAlgorithms
20.1　Minimum-CostCapacitatedFlowProblem
20.1.1　NetworkRepresentation
20.1.2　LinearProgrammingFormulation
20.1.3　CapacitatedNetworkSimplexAlgorithm
20.2　DecompositionAlgorithm
20.3　KarmarkarInterior-PointMethod
20.3.1　BasicIdeaoftheInterior-PointAlgorithm
20.3.2　Interior-PointAlgorithm
References

Chapter21　ForecastingModels
21.1　MovingAverageTechnique
21.2　ExponentialSmoothing
21.3　Regression
References

Chapter22　ProbabilisticDynamicProgramming
22.1　AGameofChance
22.2　InvestmentProblem
22.3　MaximizationoftheEventofAchievingaGoal
References

Chapter23　MarkovianDecisionProcess
23.1　ScopeoftheMarkovianDecisionProblem
23.2　Finite-StageDynamicProgrammingModel
23.3　Infinite-StageModel
23.3.1　ExhaustiveEnumerationMethod
23.3.2　PolicyIterationMethodWithoutDiscounting
23.3.3　PolicyIterationMethodwithDiscounting
23.4　LinearProgrammingSolution
References

Chapter24　CaseAnalysis
Case1：AirlineFuelAllocationUsingOptimumTankering
Case2：OptimizationofHeartValvesProduction
Case3：SchedulingAppointmentsatAustralianTouristCommissionTradeEvents
Case4：SavingFederalTravelDollars
Case5：OptimalShipRoutingandPersonnelAssignmentforNavalRecruitmentinThailand
Case6：AllocationofOperatingRoomTimeinMountSinaiHospital
Case7：OptimizingTrailerPayloadsatPFGBuildingGlass
Case8：OptimizationofCrosscuttingandLogAllocationatWeyerhaeuser
Case9：LayoutPlanningforaComputerIntegratedManufacturing(CIM)Facility　Case10：BookingLimitsinHotelReservations
Case11：CaseysProblem：InterpretingandEvaluatingaNewTest
Case12：OrderingGolfersontheFinalDayofRyderCupMatches
Case13：InventoryDecisionsinDellsSupplyChain
Case14：AnalysisofanInternalTransportSysteminaManufacturingPlant
Case15：TelephoneSalesManpowerPlanningatQantasAirways
AppendixB　StatisticalTables
AppendixC　PartialSolutionstoAnswersProblems
AppendixD　ReviewofVectorsandMatrices
D.1　Vectors
D.1.1　DefinitionofaVector
D.1.2　Addition(Subtraction)ofVectors
D.1.3　MultiplicationofVectorsbyScalars
D.1.4　LinearlyIndependentVectors
D.2　Matrices
D.2.1　DefinitionofaMatrix
D.2.2　TypesofMatrices
D.2.3　MatrixArithmeticOperations
D.2.4　DeterminantofaSquareMatrix
D.2.5　NonsingularMatrix
D.2.6　InverseofaNonsingularMatrix
D.2.7　MethodsofComputingtheInverseofMatrix
D.2.8　MatrixManipulationsUsingExcel
D.3　QuadraticForms
D.4　ConvexandConcaveFunctions
Problems
SelectedReferences
AppendixECaseStudies

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运筹学导论

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