- Language: English
- 632 Pages
- Published: August 2010
- Region: Global
Mathematical Programming for Agricultural, Environmental, and Resource Economics
- Published: February 2011
- Region: Global
- 494 Pages
- John Wiley and Sons Ltd
Mathematical Programming Models for Agriculture, Environmental, and Resource Economics provides a comprehensive overview of mathematical programming models and their applications to real world and important problems confronting agricultural, environmental, and resource economists. Unlike most mathematical programming books, the principal focus of this text is on applications of these techniques and models to the fields of agricultural, environmental, and resource economics. The three fundamental goals of the book are to provide the reader with: (1) a level of background sufficient to apply mathematical programming techniques to real world policy and business to conduct solid research and analysis, (2) a variety of applications of mathematical programming to important problems in the areas of agricultural, environmental, and resource economics, and (3) a firm foundation for preparation to more advanced, Ph.D. level books on linear and/or nonlinear programming. Despite its introductory nature, the text places significant emphasis on real world applications of mathematical programming to decision problems. A wide array of examples and case studies are used to convey the various programming techniques available to decision analysts.
Part 1 LINEAR PROGRAMMING.
Chapter 1 INTRODUCTORY CONCEPTS AND THE GRAPHICAL APPROACH TO LINEAR PROGRAMMING.
Chapter 2 THE SIMPLEX METHOD TO SOLVING LINEAR PROGRAMMING PROBLEMS.
Chapter 3 SENSITIVITY ANALYSIS USING THE SIMPLEX METHOD AND DUALITY.
Chapter 4 FARM-LEVEL LINEAR PROGRAMMING MODELS.
Chapter 5 TRANSPORTATION AND ASSIGNMENT MODELS FOR FOOD AND AGRICULTURAL MARKETS.
Chapter 6 NATURAL RESOURCE AND ENVIRONMENTAL ECONOMICS APPLICATIONS OF LINEAR PROGRAMMING.
Part 2 RELAXING THE ASSUMPTIONS OF LINEAR PROGRAMMING.
Chapter 7 INTEGER AND BINARY PROGRAMMING.
Chapter 8 OPTIMIZATION OF NONLINEAR FUNCTIONS.
Chapter 9 GLOBAL APPROACHES TO NONLINEAR OPTIMIZATION.
Chapter 10 RISK PROGRAMMING MODELS.
Chapter 11 PRICE ENDOGENOUS MATHEMATICAL PROGRAMMING MODELS.
Chapter 12 GOAL PROGRAMMING.
Chapter 13 DYNAMIC PROGRAMMING.
Harry M. Kaiser Cornell University.
Kent D. Messer University of Delaware.