本书是一本英文影印版教材，原著是由美国决策科学学会前会长伯纳德?W.泰勒编写的一本经典著作。本书具有以下特色：? 1．对枯燥、复杂和技术化的数学问题用简明易懂的语言予以解释，兼顾严谨的数理逻辑。? 2．突出建模分析框架和基础逻辑的讲授和训练，在某种程度上实现了艺术与科学的有机融合。? 3．课后习题丰富，并配有网络题库，供自学者加强训练，及时检查对理论模型及其求解方法的掌握程度。? 第12版把修订**放在企业和组织的*技术发展上，增加了商业分析（第1章）、项目风险（第8章）以及数据挖掘（第14章）等内容。?

The objective of management science is to solve the decision-making problems that confront and confound managers in both the public and the private sector by developing mathematical models of those problems. These models have traditionally been solved with various mathematical techniques, all of which lend themselves to specific types of problems. Thus, management science as a field of study has always been inherently mathematical in nature, and as a result sometimes complex and rigor- ous. When I began writing the first edition of this book in 1979, my main goal was to make these mathematical top- ics seem less complex and thus more palatable to under- graduate business students. To achieve this goal I started out by trying to provide simple, straightforward explana- tions of often difficult mathematical topics. I tried to use lots of examples that demonstrated in detail the funda- mental mathematical steps of the modeling and solution techniques. Although in the past three decades the empha- sis in management science has shifted away from strictly mathematical to mostly computer solutions, my objective has not changed. I have provided clear, concise explana- tions of the techniques used in management science to model problems, and provided many examples of how to solve these models on the computer while still including some of the fundamental mathematics of the techniques.
The stuff of management science can seem abstract, and students sometimes have trouble perceiving the use- fulness of quantitative courses in general. I remember that when I was a student, I could not foresee how I would use such mathematical topics (in addition to a lot of the other things I learned in college) in any job after graduation. Part of the problem is that the examples used in books often do not seem realistic. Unfortunately, examples must be made simple to facilitate the learning process. Larger, more complex examples reflecting actual applications would be too complex to help th

Preface i 1Management Science1 The Management Science Approach to Problem Solving2 Time Out: for Pioneers in Management Science5 Management Science Application: Room Pricing with Management Science at Marriott6 Management Science and Business Analytics7 Model Building: Break-Even Analysis8 Computer Solution12 Management Science Modeling Techniques15 Management Science Application: The Application of Management Science with Spreadsheets16 Business Usage of Management Science Techniques18 Management Science Application: Management Science in Health Care19 Management Science Application: Allocating Seat Capacity on Indian Railways Using Linear Programming32 Graphical Solutions of Linear Programming Models32 Management Science Application: Renewable Energy Investment Decisions at GE Energy44 A Minimization Model Example44 Management Science Application: Determining Optimal Fertilizer Mixes at Soquimich (South America)48 Irregular Types of Linear Programming Problems50 Characteristics of Linear Programming Problems53 Summary 54 ? Example Problem Solutions 54 ? Problems 58 ? Case Problems 60 3Linear Programming: Computer Solution and Sensitivity Analysis63 Management Science Models in Decision Support Systems20 Summary 21 ? Problems 22 ? Case Problems 24 2Linear Programming: Model Formulation and Graphical Solution27 Model Formulation28 A Maximization Model Example28 Time Out: for George B. Dantzig29 Computer Solution64 Management Science Application: Scheduling Air Ambulance Service in Ontario (Canada)69 Management Science Application: Improving Profitability at Norske Skog with Linear Programming70 Sensitivity Analysis71 Summary 82 ? Example Problem Solution 82 ? Problems 85 ? Case Problems 89 i iiCONTENTS 4Linear Programming: Modeling Examples92 A Product Mix Exampl