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Informationen zum Autor H. Paul Williams , London School of Economics, UK. Klappentext The 5th edition of Model Building in Mathematical Programming discusses the general principles of model building in mathematical programming and demonstrates how they can be applied by using several simplified but practical problems from widely different contexts. Suggested formulations and solutions are given together with some computational experience to give the reader a feel for the computational difficulty of solving that particular type of model. Furthermore, this book illustrates the scope and limitations of mathematical programming, and shows how it can be applied to real situations. By emphasizing the importance of the building and interpreting of models rather than the solution process, the author attempts to fill a gap left by the many works which concentrate on the algorithmic side of the subject. Zusammenfassung The 5th edition of Model Building in Mathematical Programming discusses the general principles of model building in mathematical programming and demonstrates how they can be applied by using several simplified but practical problems from widely different contexts. Inhaltsverzeichnis Preface PART 1 1 Introduction 1.1 The Concept of a Model 1.2 Mathematical Programming Models 2 Solving Mathematical Programming Models 2.1 Algorithms and Packages 2.2 Practical Considerations 2.3 Decision Support and Expert Systems 2.4 Constraint Programming 3 Building Linear Programming Models 3.1 The Importance of Linearity 3.2 Defining Objectives 3.3 Defining Constraints 3.4 How to Build a Good Model 3.5 The Use of Modelling Languages 4 Structured Linear Programming Models 4.1 Multiple Plant, Product, and Period Models 4.2 Stochastic Programming Models 4.3 Decomposing a Large Model 5 Applications and Special Types of Mathematical Programming Model 5.1 Typical Applications 5.2 Economic Models 5.3 Network Models 5.4 Converting Linear Programs to Networks 6 Interpreting and Using the Solution of a Linear Programming Model 6.1 Validating a Model 6.2 Economic Interpretations 6.3 Sensitivity Analysis and the Stability of a Model 6.4 Further Investigations Using a Model 6.5 Presentation of the Solutions 7 Non-linear Models 7.1 Typical Applications 7.2 Local and Global Optima 7.3 Separable Programming 7.4 Converting a Problem to a Separable Model 8 Integer Programming 8.1 Introduction 8.2 The Applicability of Integer Programming 8.3 Solving Integer Programming Models 9 Building Integer Programming Models I 9.1 The Uses of Discrete Variables 9.2 Logical Conditions and Zero-One Variables 9.3 Special Ordered Sets of Variables 9.4 Extra Conditions Applied to Linear Programming Models 9.5 Special Kinds of Integer Programming Model 9.6 Column Generation 10 Building Integer Programming Models II 10.1 Good and Bad Formulations 10.2 Simplifying an Integer Programming Model 10.3 Economic Information Obtainable by Integer Programming 10.4 Sensitivity Analysis and the Stability of a Model 10.5 When and How to Use Integer Programming 11 The Implementation of a Mathematical Programming System of Planning 11.1 Acceptance and Implementation 11.2 The Unification of Organizational Functions 11.3 Centralization versus Decentralization 11.4 The Collection of Data and the Maintenance of a Model PART 2 12 The Problems 12.1 Food Manufacture 1 When to buy and how to blend 12.2 Food Manufacture 2 Limiting the number of ingredients and adding extra conditions 12.3 Factory Planning 1
