哈姆迪·塔哈著的《运筹学基础(英文版第10版全新版)/管理科学与工程经典丛书》是运筹学经典著作Operations research: an introduction的英文影印版。该书英文版自中国人民大学出版社引进出版以来，受到国内读者的广泛关注和好评，被许多高校选为“运筹学”双语课程或全英文课程的参考书。
本书的主要特色在于：（1）重视运筹学基本知识的讲解，对高深问题也做了较深入的分析，以满足不同读者的需要。（2）突出实用性。各章通过实践问题的求解导出运筹问题的数学模型，既凸显该运筹问题的实际背景，也便于读者学习建模。（3）增加了运筹学中重要理论与应用的重大事件介绍。（4）计算方法与软件相结合。全书使用教学辅助软件TORA、软件包Excel及AMPL等，读者可以利用这些软件工具对所学的模型和计算方法进行计算和检验。

哈姆迪·塔哈(Hamdy A．Taha)，美国阿肯色大学荣誉退休的工业工程教授，曾负责运筹学以及模拟方面的教学与科研工作，获得该校Alumni Award科研成果奖以及Nadine Baum优秀教学奖等。撰有相关领域的专著，并被译成多种语言出版。在European Journal of operatfons Research，IEEE Trans-actions on Reliability等杂志上发表多篇学术论文。

Chapter 1 What Is Operations Research?
1.1 Introduction
1.2 Operations Research Models
1.3 Solvinq the OR Model
1.4 Queuing and Simulation Models
1.5 Art of Modeling
1.6 More than Just Mathematics
1.7 Phases of an OR Study
1.8 About this Book
Bibliography
Problems
Chapter 2 Modeling with Linear Programming
2.1 Two-Variable LP Model
2.2 Graphical LP Solution
2.3 Computer Solution with Solver and AMPL
2.4 Linear Programming Applications
Bibliography
Problems
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 Startinq Solution
3.5 Special Cases in the Simplex Method
3.6 Sensitivity Analysis
3.7 Computational Issues in Linear Programming
Bibliography
Case Study: Optimization of Heart Valves Production
Problems
Chapter 4 Duality and Post-optima Analysis
4.1 Definition of the Dual Problem
4.2 Primal-Dual Relationshlps
4.3 Economic Interpretation of Duality
4.4 Additional Simplex Algorithms
4.5 Post-Optimal Analysis
Bibliography
Problems
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
Bibliography
Case Study：Scheduling Appointments at Australian
Tourist Commission Trade Events
Problems
Chapter 6 Network Model
6.1 Scope and Definition of Network Models
6.2 MinimaI Spanning Tree Algorithm
6.3 Shortest-Route Problem
6.4 Maximal Flow Model
6.5 CPM and Pert
Bibliography
Case Study: Saving Federal Travel Dollars
Problems
Chapter 7 Goal programming
7.1 A Goal Programming Formulation
7.2 Goal Programming Algorithms
Bibliography
Case Study: Allocation of Operating Room Time in Mount Sinai Hospital
Problems
Chapter 8 Integer Linear Programming
8.1 Illustrative Applications
8.2 Integer Programming Algorithms
Bibliography
Problems
Chapter 9 Heuristic Programming
9.1 Introduction
9.2 Greedy (Local Search) Heuristics
9.3 Metaheuristic
9.4 Application of Metaheuristics to Integer Linear Programs
9.5 Introduction to Constraint Programming (CP)
Bibliography
Problems
Chapter 10 Deterministic Dynamic Programming
10.1 Recursive Nature of Dynamic Programming (DP) Computations
10.2 Forward and Backward Recursion
10.3 Selected DP Applications
10.4 Problem of Dimensionality
Bibliography
Case Study: Optimization of Crosscutting and Log Allocation at Weyerhaeuser
Problems
Chapter 11 Inventory Modeling (with Introduction to Supply Chains)
11.1 lnventory Problem: A Supply Chain Perspective
11.2 Role of Demand in the Development of lnventory Models
11.3 Static Economic-Order-Quantity Models
11.4 Dynamic EOQ Models
11.5 Sticky Issues in InVentory Modeling
Bibliography
Case Study：Kroger Improves Pharmacy Inventory Management Problems
Chapter 12 Decision Analysis and Games
12.1 Decision Making Under Certainty—Analytic Hierarchy Process (AHP)
12.2 Decision Making Under Risk
12.3 Decision Under Uncertainty
12.4 Game Theory
Bibliography
Case Study: Booking Limits in Hotel Reservations
Problems
Chapter 13 Probabilictic Inventory Models
13.1 Continuous Review Models
13.2 Single-Period Models
13.3 Multiperiod Model
Bibliography
Problems
Chapter 14 Queuing Systems
14.1 Why Study Queues?
14.2 Elements of a Queuing Model
14.3 Role of Exponential Distribution
14.4 Pure Birth and Death Models (Relationship Between the Exponential and Poisson Distributions)
14.5 General Poisson Queuing Model
14.6 Specialized Poisson Queues
14.7 (M/G/1):(GD/∞/∞)——Pollaczek-Khintchine (P-K) Formula
14.8 Other Queuing Models
14.9 Queuing Decis