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Operations Research : An Introduction / Hamdy A. Taha.

By: Material type: TextTextPublisher: Upper Saddle River, N.J. ; London : Pearson/Prentice Hall, [2007]Copyright date: ©2007Edition: Eighth EditionDescription: xx, 813 pages : illustrations ; 25 cm. + 1 CD-ROM (4 3/4 in.)Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0131889230 (cased) :
  • 9780131889231
Subject(s): DDC classification:
  • 658.4034 23 T.H.O.
LOC classification:
  • T57.6 .T3 2007
Contents:
Chapter 1: What is Operations Research? 1.1 Operations Research Models 1.2 Solving the OR Model 1.3 Queueing and Simulation Models 1.4 Art of Modeling 1.5 More than Just Mathematics 1.6 Phases of an OR Study 1.7 About this Book Problems References -- Chapter 2: Modeling with Linear Programming 2.1 Two-Variable LP Model 2.2 Graphical LP Solution 2.3 Selected LP Applications 2.4 Computer Solution with Solver and AMPL Problems References -- Chapter 3: The Simplex Method and Sensitivity Analysis 3.1 LP Model in Equation Form 3.2 Transition from Graphical to Algebraic Solution 3.3 The Simplex Method 3.4 Artificial Starting Solution 3.5 Special Cases in the Simplex Method 3.6 Sensitivity Analysis Problems References -- Chapter 4: Duality and Post-Optimal Analysis 4.1 Definition of the Dual Problem 4.2 Primal-Dual Relationships 4.3 Economic Interpretation of Duality 4.4 Additional Simplex Algorithms 4.5 Post-Optimal Analysis Problems References -- Chapter 5: Transportation Model and its Variants 5.1 Definition of the Transportation Model 5.2 Nontraditional Transportation Models 5.3 The Transportation Algorithm 5.4 The Assignment Model 5.5 The Transshipment Model Problems References -- Chapter 6: Network Models 6.1 Scope and Definition of Network Models 6.2 Minimal Spanning Tree Algorithm 6.3 Shortest-Route Problem 6.4 Maximal Flow Model 6.5 CPM and PERT Problems References -- Chapter 7: Advanced Linear Programming 7.1 Simplex Method Fundamentals 7.2 Revised Simplex Method 7.3 Bounded Variables Algorithm 7.4 Duality 7.5 Parametric Linear Programming Problems References -- Chapter 8: Goal Programming 8.1 A Goal Programming Formulation 8.2 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 Problems References Appendix A: AMPL Modeling Language A.1 Rudimentary AMPL Mode l A.2 Components of AMPL Model A.3 Mathematical Expressions and Computed Parameters A.4 Subsets and Indexed Sets A.5 Accessing External Files A.6 Interactive Commands A.7 Iterative and Conditional Execution of AMPL Commads A.8 Sensitivity Analysis Using AMPL Reference -- Appendix B: Statistical Tables -- Appendix C: Partial Answers to Selected Problems Index On the CD -- Chapter 20: Additional Network and LP Algorithms20.1 Minimim-Cost Capacitated Flow Problem20.2 Decomposition Alogrithm20.3 Karmarkar Interior-Point Method Problems References -- Chapter 21: Forecasting Models21.1 Moving Average Technique21.2 Exponential Smoothing21.3 Maximization of the Event of Achieving a Goal Problems References -- Chapter 22: Probabilistic Dynamic Programming22.1 A Game of Chance22.2 Investment Problem22.3 Maximization of the Event of Achieving a Goal Problems References -- Chapter 23: Markovian Decision Process23.1 Scope of the Markovian Decision Problem23.2 Finite-Stage Dynamic Programming Model23.3 Infinite-Stage Model23.4 Linear Programming Solution Problems References -- Chapter 24: Case AnalysisCase 1: Airline Fuel Allocation Using Optimum TankeringCase 2: Optimization of Heart Valves ProductionCase 3: Scheduling Appointments at Australian Tourist Commission Trade EventsCase 4: Saving Federal Travel DollarsCase 5: Optimal Ship Routing and Personnel Assignments for Naval Recruitment in ThailandCase 6: Allocation of Operating Room Time in Mount Sinai HospitalCase 7: Optimizing Trailer Payloads at PFG Building GlassCase 8: Optimization of Crosscutting and Log Allocation at WeyerhaeuserCase 9: Layout Planning of a Computer Integrated Manufacturing (CIM) FacilityCase 10: Booking Limits in Hotel ReservationsCase 11: Casey's Problem: Interpreting and Evaluating a New TestCase 12: Ordering Golfers on the Final Day of Ryder Cup MatchesCase 13: Inventory Decisions in Dell's Supply ChainCase 14: Analysis of an Internal Transport System in a Manufacturing PlantCase 15: Telephone Sales Manpower Planning at Qantas Airways -- Appendix D: Review of Vectors and MatricesD.1 VectorsD.2 MatricesD.3 Quadratic FormsD.4 Convex and Concave Functions Problems References Appendix E: Case Studies.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books Media and mass communication Library Q4 658.4034 T.H.O. Available E0000560
Books Books Media and mass communication Library Q4 658.4034 T.H.O. Available E0000292
CD / DVD with book CD / DVD with book Media and mass communication Library 658.4034 T.H.O. Available
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Includes bibliographical references and index.

Chapter 1: What is Operations Research? 1.1 Operations Research Models 1.2 Solving the OR Model 1.3 Queueing and Simulation Models 1.4 Art of Modeling 1.5 More than Just Mathematics 1.6 Phases of an OR Study 1.7 About this Book Problems References -- Chapter 2: Modeling with Linear Programming 2.1 Two-Variable LP Model 2.2 Graphical LP Solution 2.3 Selected LP Applications 2.4 Computer Solution with Solver and AMPL Problems References -- Chapter 3: The Simplex Method and Sensitivity Analysis 3.1 LP Model in Equation Form 3.2 Transition from Graphical to Algebraic Solution 3.3 The Simplex Method 3.4 Artificial Starting Solution 3.5 Special Cases in the Simplex Method 3.6 Sensitivity Analysis Problems References -- Chapter 4: Duality and Post-Optimal Analysis 4.1 Definition of the Dual Problem 4.2 Primal-Dual Relationships 4.3 Economic Interpretation of Duality 4.4 Additional Simplex Algorithms 4.5 Post-Optimal Analysis Problems References -- Chapter 5: Transportation Model and its Variants 5.1 Definition of the Transportation Model 5.2 Nontraditional Transportation Models 5.3 The Transportation Algorithm 5.4 The Assignment Model 5.5 The Transshipment Model Problems References -- Chapter 6: Network Models 6.1 Scope and Definition of Network Models 6.2 Minimal Spanning Tree Algorithm 6.3 Shortest-Route Problem 6.4 Maximal Flow Model 6.5 CPM and PERT Problems References -- Chapter 7: Advanced Linear Programming 7.1 Simplex Method Fundamentals 7.2 Revised Simplex Method 7.3 Bounded Variables Algorithm 7.4 Duality 7.5 Parametric Linear Programming Problems References -- Chapter 8: Goal Programming 8.1 A Goal Programming Formulation 8.2 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 Problems References Appendix A: AMPL Modeling Language A.1 Rudimentary AMPL Mode l A.2 Components of AMPL Model A.3 Mathematical Expressions and Computed Parameters A.4 Subsets and Indexed Sets A.5 Accessing External Files A.6 Interactive Commands A.7 Iterative and Conditional Execution of AMPL Commads A.8 Sensitivity Analysis Using AMPL Reference -- Appendix B: Statistical Tables -- Appendix C: Partial Answers to Selected Problems Index On the CD -- Chapter 20: Additional Network and LP Algorithms20.1 Minimim-Cost Capacitated Flow Problem20.2 Decomposition Alogrithm20.3 Karmarkar Interior-Point Method Problems References -- Chapter 21: Forecasting Models21.1 Moving Average Technique21.2 Exponential Smoothing21.3 Maximization of the Event of Achieving a Goal Problems References -- Chapter 22: Probabilistic Dynamic Programming22.1 A Game of Chance22.2 Investment Problem22.3 Maximization of the Event of Achieving a Goal Problems References -- Chapter 23: Markovian Decision Process23.1 Scope of the Markovian Decision Problem23.2 Finite-Stage Dynamic Programming Model23.3 Infinite-Stage Model23.4 Linear Programming Solution Problems References -- Chapter 24: Case AnalysisCase 1: Airline Fuel Allocation Using Optimum TankeringCase 2: Optimization of Heart Valves ProductionCase 3: Scheduling Appointments at Australian Tourist Commission Trade EventsCase 4: Saving Federal Travel DollarsCase 5: Optimal Ship Routing and Personnel Assignments for Naval Recruitment in ThailandCase 6: Allocation of Operating Room Time in Mount Sinai HospitalCase 7: Optimizing Trailer Payloads at PFG Building GlassCase 8: Optimization of Crosscutting and Log Allocation at WeyerhaeuserCase 9: Layout Planning of a Computer Integrated Manufacturing (CIM) FacilityCase 10: Booking Limits in Hotel ReservationsCase 11: Casey's Problem: Interpreting and Evaluating a New TestCase 12: Ordering Golfers on the Final Day of Ryder Cup MatchesCase 13: Inventory Decisions in Dell's Supply ChainCase 14: Analysis of an Internal Transport System in a Manufacturing PlantCase 15: Telephone Sales Manpower Planning at Qantas Airways -- Appendix D: Review of Vectors and MatricesD.1 VectorsD.2 MatricesD.3 Quadratic FormsD.4 Convex and Concave Functions Problems References Appendix E: Case Studies.

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