Model Building in Mathematical Programming.

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 solution...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Williams, H. Paul
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Wiley, 2013.
Temas:
Programming (Mathematics)
Mathematical models.
Programmation (Mathématiques)
Modèles mathématiques.
mathematical models.
BUSINESS & ECONOMICS > Management Science.
Mathematical models
Electronic books.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Title Page
  • Copyright
  • Dedication
  • Preface
  • Preface to the Fifth Edition
  • Part I
  • Chapter 1: Introduction
  • 1.1 The concept of a model
  • 1.2 Mathematical programming models
  • Chapter 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 (CP)
  • Chapter 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
  • Chapter 4: Structured linear programming models
  • 4.1 Multiple plant, product and period models
  • 4.2 Stochastic programmes
  • 4.3 Decomposing a large model
  • Chapter 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
  • Chapter 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
  • Chapter 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
  • Chapter 8: Integer programming
  • 8.1 Introduction
  • 8.2 The applicability of integer programming
  • 8.3 Solving integer programming models
  • Chapter 9: Building integer programming models I
  • 9.1 The uses of discrete variables
  • 9.2 Logical conditions and 0-1 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
  • Chapter 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
  • Chapter 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 II
  • Chapter 12: The problems
  • 12.1 Food manufacture 1
  • 12.2 Food manufacture 2
  • 12.3 Factory planning 1
  • 12.4 Factory planning 2
  • 12.5 Manpower planning
  • 12.6 Refinery optimisation
  • 12.7 Mining
  • 12.8 Farm planning
  • 12.9 Economic planning
  • 12.10 Decentralisation
  • 12.11 Curve fitting
  • 12.12 Logical design
  • 12.13 Market sharing
  • 12.14 Opencast mining
  • 12.15 Tariff rates (power generation)

Ejemplares similares