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Operations research : an introduction / Hamdy A. Taha.

By: Material type: TextTextPublication details: New Delhi : Pearson/Prentice Hall, 2007Edition: 8th edDescription: 833 p. ill. ; 25 cm. + 1 CD-ROM (4 3/4 in.)ISBN:
  • 9798131705154
Subject(s): DDC classification:
  • 658.4/034 22 T1286
Contents:
Chapter 1: What is Operations Research?1.1 Operations Research Models1.2 Solving the OR Model1.3 Queueing and Simulation Models1.4 Art of Modeling1.5 More than Just Mathematics1.6 Phases of an OR Study1.7 About this Book Problems References Chapter 2: Modeling with Linear Programming2.1 Two-Variable LP Model2.2 Graphical LP Solution2.3 Selected LP Applications2.4 Computer Solution with Solver and AMPL Problems References Chapter 3: The Simplex Method and Sensitivity Analysis3.1 LP Model in Equation Form3.2 Transition from Graphical to Algebraic Solution3.3 The Simplex Method3.4 Artificial Starting Solution3.5 Special Cases in the Simplex Method 3.6 Sensitivity Analysis Problems References Chapter 4: Duality and Post-Optimal Analysis4.1 Definition of the Dual Problem4.2 Primal-Dual Relationships4.3 Economic Interpretation of Duality4.4 Additional Simplex Algorithms 4.5 Post-Optimal Analysis Problems References Chapter 5: Transportation Model and its Variants5.1 Definition of the Transportation Model5.2 Nontraditional Transportation Models5.3 The Transportation Algorithm5.4 The Assignment Model5.5 The Transshipment Model Problems References Chapter 6: Network Models6.1 Scope and Definition of Network Models6.2 Minimal Spanning Tree Algorithm6.3 Shortest-Route Problem6.4 Maximal Flow Model6.5 CPM and PERT Problems References Chapter 7: Advanced Linear Programming7.1 Simplex Method Fundamentals 7.2 Revised Simplex Method7.3 Bounded Variables Algorithm7.4 Duality7.5 Parametric Linear Programming Problems References Chapter 8: Goal Programming8.1 A Goal Programming Formulation8.2 Goal Programming Algorithms Problems References Chapter 9: Integer Linear Programming9.1 Illustrative Applications9.2 Integer Programming Algorithms9.3 Traveling Salesperson (TSP) Problem Problems References Chapter 10: Deterministic Dynamic Programming10.1 Recursive Nature of Computations in DP10.2 Forward and Backward Recursion10.3 Selected DP Applications10.4 Problem of Dimensionality Problems References Chapter 11: Deterministic Inventory Models11.1 General Inventory Model11.2 Role of Demand in the Development of Inventory Models11.3 Static Economic-Order-Quantity (EOQ) Models11.4 Dynamic EOQ Models Problems References Chapter 12: Review of Basic Probability12.1 Laws of Probability12.2 Random Variables and Probability Distributions12.3 Expectation of a Random Variable 12.4 Four Common Probability Distributions12.5 Empirical Distributions Problems References Chapter 13: Decision Analysis and Games13.1 Decision Making under Certainty-Analytic Hierarchy Process (AHP)13.2 Decision Making under Risk13.3 Decision under Uncertainty13.4 Game Theory Problems References Chapter 14: Probabilistic Inventory Models14.1 Continuous Review Models14.2 Single-Period Models14.3 Multiperiod Model Problems References Chapter 15:Queueing Systems15.1 Why Study Queues?15.2 Elements of a Queuing Model15.3 Role of Exponential Distribution15.4 Pure Birth and Death Models (Relationship between the Exponential and Poisson Distributions)15.5 Generalized Poisson Queuing Model15.6 Specialized Poisson Queues15.7 (M/G/1):(GD/Inf/Inf)-Pollaczek-Khintchine (P-K) Formula15.8 Other Queuing Models15.9 Queueing Decision Models Problems References Chapter 16: Simulation Modeling16.1 Monte Carlo Simulation16.2 Types of Simulation16.3 Elements of Discrete-Event Simulation16.4 Generation of Random Numbers16.5 Mechanics of Discrete Simulation16.6 Methods for Gathering Statistical Observations16.7 Simulation Languages Problems References Chapter 17: Markov Chains17.1 Definition of a Markov Chain17.2 Absolute and n-Step Transition Probabilities17.3 Classification of the States in a Markov Chain17.4Steady-State Probabilities and Mean Return Times of Ergodic Chains17.5 First Passage Time17.6 Analysis of Absorbing States Problems References Chapter 18: Classical Optimization Theory18.1 Unconstrained Problems18.2 Constrained Problems Problems References Chapter 19: Nonlinear Programming Algorithms19.1 Unconstrained Algorithms19.2 Constrained Algorithms
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Books Books UE-Central Library 658.4034 T1286 (Browse shelf(Opens below)) Available T2381

includes appendix and index

Chapter 1: What is Operations Research?1.1 Operations Research Models1.2 Solving the OR Model1.3 Queueing and Simulation Models1.4 Art of Modeling1.5 More than Just Mathematics1.6 Phases of an OR Study1.7 About this Book Problems References Chapter 2: Modeling with Linear Programming2.1 Two-Variable LP Model2.2 Graphical LP Solution2.3 Selected LP Applications2.4 Computer Solution with Solver and AMPL Problems References Chapter 3: The Simplex Method and Sensitivity Analysis3.1 LP Model in Equation Form3.2 Transition from Graphical to Algebraic Solution3.3 The Simplex Method3.4 Artificial Starting Solution3.5 Special Cases in the Simplex Method 3.6 Sensitivity Analysis Problems References Chapter 4: Duality and Post-Optimal Analysis4.1 Definition of the Dual Problem4.2 Primal-Dual Relationships4.3 Economic Interpretation of Duality4.4 Additional Simplex Algorithms 4.5 Post-Optimal Analysis Problems References Chapter 5: Transportation Model and its Variants5.1 Definition of the Transportation Model5.2 Nontraditional Transportation Models5.3 The Transportation Algorithm5.4 The Assignment Model5.5 The Transshipment Model Problems References Chapter 6: Network Models6.1 Scope and Definition of Network Models6.2 Minimal Spanning Tree Algorithm6.3 Shortest-Route Problem6.4 Maximal Flow Model6.5 CPM and PERT Problems References Chapter 7: Advanced Linear Programming7.1 Simplex Method Fundamentals 7.2 Revised Simplex Method7.3 Bounded Variables Algorithm7.4 Duality7.5 Parametric Linear Programming Problems References Chapter 8: Goal Programming8.1 A Goal Programming Formulation8.2 Goal Programming Algorithms Problems References Chapter 9: Integer Linear Programming9.1 Illustrative Applications9.2 Integer Programming Algorithms9.3 Traveling Salesperson (TSP) Problem Problems References Chapter 10: Deterministic Dynamic Programming10.1 Recursive Nature of Computations in DP10.2 Forward and Backward Recursion10.3 Selected DP Applications10.4 Problem of Dimensionality Problems References Chapter 11: Deterministic Inventory Models11.1 General Inventory Model11.2 Role of Demand in the Development of Inventory Models11.3 Static Economic-Order-Quantity (EOQ) Models11.4 Dynamic EOQ Models Problems References Chapter 12: Review of Basic Probability12.1 Laws of Probability12.2 Random Variables and Probability Distributions12.3 Expectation of a Random Variable 12.4 Four Common Probability Distributions12.5 Empirical Distributions Problems References Chapter 13: Decision Analysis and Games13.1 Decision Making under Certainty-Analytic Hierarchy Process (AHP)13.2 Decision Making under Risk13.3 Decision under Uncertainty13.4 Game Theory Problems References Chapter 14: Probabilistic Inventory Models14.1 Continuous Review Models14.2 Single-Period Models14.3 Multiperiod Model Problems References Chapter 15:Queueing Systems15.1 Why Study Queues?15.2 Elements of a Queuing Model15.3 Role of Exponential Distribution15.4 Pure Birth and Death Models (Relationship between the Exponential and Poisson Distributions)15.5 Generalized Poisson Queuing Model15.6 Specialized Poisson Queues15.7 (M/G/1):(GD/Inf/Inf)-Pollaczek-Khintchine (P-K) Formula15.8 Other Queuing Models15.9 Queueing Decision Models Problems References Chapter 16: Simulation Modeling16.1 Monte Carlo Simulation16.2 Types of Simulation16.3 Elements of Discrete-Event Simulation16.4 Generation of Random Numbers16.5 Mechanics of Discrete Simulation16.6 Methods for Gathering Statistical Observations16.7 Simulation Languages Problems References Chapter 17: Markov Chains17.1 Definition of a Markov Chain17.2 Absolute and n-Step Transition Probabilities17.3 Classification of the States in a Markov Chain17.4Steady-State Probabilities and Mean Return Times of Ergodic Chains17.5 First Passage Time17.6 Analysis of Absorbing States Problems References Chapter 18: Classical Optimization Theory18.1 Unconstrained Problems18.2 Constrained Problems Problems References Chapter 19: Nonlinear Programming Algorithms19.1 Unconstrained Algorithms19.2 Constrained Algorithms

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