Fr. 80.00

Model Building in Mathematical Programming

English · Paperback / Softback

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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

List of contents

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 ProgrammingModel5.1 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 ProgrammingModel

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 ofPlanning

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 extraconditions

12.3 Factory Planning 1

What to make, on what machines, and when

12.4 Factory Planning 2

When should machines be down for maintenance

12.5 Manpower Planning

How to recruit, retrain, make redundant, or overman

12.6 Refinery Optimization

How to run an oil refinery

12.7 Mining

Which pits to work and when to close them down

12.8 Farm Planning

How much to grow and rear

12.9 Economic Planning

How should an economy grow

12.10 Decentralization

How to disperse offices from the capital

12.11 Curve Fitting

Fitting a curve to a set of data points

12.12 Logical Design

Constructing an electronic system with a minimum number ofcomponents

12.13 Market Sharing

Assigning retailers to company divisions

12.14 Opencast Mining

How much to excavate

12.15 Tariff Rates (Power Generation)

How to determine tariff rates for the sale of electricity

12.16 Hydro Power

How to generate and combine hydro and thermal electricitygeneration

12.17 Three-dimensional Noughts and Crosses

A combinatorial problem

12.18 Optimizing a Constraint

Reconstructing an integer programming constraint more simply

12.19 Distribution 1

Which factories and depots to supply which customers

12.20 Depot Location (Distribution 2)

Where should new depots be built

12.21 Agricultural Pricing

What prices to charge for dairy products

12.22 Efficiency Analysis

How to use data envelopment analysis to compare efficiencies ofgarages

12.23 Milk Collection

How to route and

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