Mathematical programming for agricultural, environmental, and resource economics / Harry M. Kaiser and Kent D. Messer.

Includes bibliographical references and index.

Machine generated contents note: Preface -- PART 1. LINEAR PROGRAMMING -- Chapter 1: Introductory Concepts and the Graphical Approach to Linear Programming -- 1.1 Applications of Linear Programming in Agriculture, Environment, and Resources Economics -- 1.2 Components of the General Form for the Model -- 1.3 Standard Assumptions of Linear Programming Models -- 1.4 Formulating Linear Programming Problems -- 1.5 The Graphical Approach for Solving Linear Programming Maximization Problems -- 1.6 The Graphical Approach for Solving Linear Programming Minimization Problems -- 1.7 Sensitivity Analysis with the Graphical Approach -- 1.8 Summary -- 1.9 Exercises -- Chapter 2: The Simplex Method to Solving Linear Programming Problems -- 2.1 The Simplex Method for a Simple Maximization Problem -- 2.2 The Simplex Method for Maximization Problems: General Case -- 2.3 The Simplex Method and Minimization Problems -- 2.4 Summary -- 2.5 Exercises -- Chapter 3: Sensitivity Analysis using the Simplex Method and Duality -- 1. Simplex-Based Sensitivity Analysis for Maximization Problems -- 3.2 Simplex-Based Sensitivity Analysis for Minimization Problems -- 3.3 Duality -- 3.4 Solving LP Problems Using Solver -- 3.5 Summary -- 3.6 Appendix: Summation and Matrix Notation -- 3.5 Exercises -- Chapter 4: Farm-Level Linear Programming Models -- 4.1 Static Models of a Crop Farm -- 4.2 Dynamic Models -- 4.3 Crop-Livestock Enterprises -- 4.4 Model Validation -- 4.5 Research Application: Crop Farm Model -- 4.6 Research Application: Economic Feasibility of an Energy Crop on a South Alabama Cotton-Peanut Farm -- 4.7 Summary -- 4.8 Exercises -- Chapter 5: Transportation and Assignment Models for Food and Agricultural Markets -- 5.1 General Transportation Model -- 5.2 Extensions to the Model -- 5.3 The Transshipment Model -- 5.4 The Assignment Model -- 5.5 Research Application: U.S. Dairy Sector Simulator -- 5.6 Summary -- 5.7 Exercises -- Chapter 6: Resource and Environmental Economics Applications of Linear Programming -- 6.1 Linear Programming Applications in Land Use Planning -- 6.2 Optimal Stocking Problem for a Game Ranch -- 6.3 Efficient Irrigation and Cropping Patterns: A Linear Programming Example -- 6.4 Research Application: Optimizing Grizzly Bear Corridor Design -- 6.5 Summary -- 6.6 Exercises -- PART 2. RELAXING THE ASSUMPTION OF LINEAR PROGRAMMING -- Chapter 7: Integer and Binary Programming -- 7.1 Background on Integer programming -- 7.2 The Branch and Bound Solution Procedure -- 7.3 Mixed-integer Programs -- 7.4 Solver's Integer and Binary Programming Options -- 7.5 Capital Budgeting Problems - A Case of Water Conservation -- 7.6 Distribution System Design -- 7.7 Sensitivity Analysis in Integer Programming -- 7.8 Research Application: Optimizing Agricultural Land Protection in Delaware -- 7.9 Comparison of Sequential and Simultaneous Approaches to Binary Linear Programming -- 7.10 Summary -- 7.11 Exercises -- Chapter 8: Optimization of Nonlinear Functions -- 8.1 Slopes of Functions -- 8.2 Shortcut Formulas for Derivatives -- 8.3 Unconstrained Optimization -- 8.4 Multivariate Functions -- 8.5 Constrained Optimization with Equality Constraints -- 8.6 Kuhn-Tucker Conditions and Constrained Optimization with Inequality Constraints -- 8.7 Solving Constrained Optimization Problems with Solver -- 8.8 Research Application: Optimal Advertising -- 8.9 Research Application: Water Pollution Abatement Policies -- 8.10 Summary -- 8.11 Exercises -- Chapter 9: Global Approaches to Nonlinear Optimization -- 9.1 Development of Nonlinear Problems -- 9.2 SOCP Barrier Solver -- 9.3 Evolutionary Solver -- 9.4 Interval Global Solver -- 9.5 A Forestry Example Using Nonlinear Excel Functions -- 9.6 Research Applications: Crop Farming in Northeast Australia -- 9.7 Research Applications: An Analysis of Energy Market Deregulation -- 9.8 Summary -- 9.9 Exercises -- Chapter 10: Risk Programming Models -- 10.1 Expected Value, Variance, and Covariance -- 10.2 Agricultural Decision Analysis under Risk and Uncertainty -- 10.3 Quadratic Risk Programming -- 10.4 Linearized Version of Quadratic Risk Programming -- 10.5 Target MOTAD -- 10.6 Chance Constrained Programming -- 10.7 Discrete Stochastic Sequential Programming -- 10.8 Issues in Measuring Risk in Risk Programming -- 10.9 Research Application: Quadratic Risk Programming -- 10.10 Research Application: Discrete Stochastic Sequential Programming -- 10.11 Research Application: Agriculture and Climate Change -- 10.12 Summary -- 10.13 Exercises -- Chapter 11: Price Endogenous Mathematical Programming Models -- 11.1 The Market under Perfect Competition -- 11.2 The Market under Monopoly/Monopsony and Imperfect Competition -- 11.3 Spatial Equilibrium Models -- 11.4 Industry Models -- 11.5 Research Application: A Spatial Equilibrium Model for Imperfectly Competitive Milk Markets -- 11.6 Research Application: Climate Change and U.S. Agriculture -- 11.7 Summary -- 11.8 Exercises -- Chapter 12: Goal Programming -- 12.1 Goal Programming -- 12.2 Non-preemptive Goal Problem -- 12.3 Preemptive Goal Programming -- 12.4 Deriving Weights for Goal Programming -- 12.5 Research Application: Optimal Parasite Control Programs -- 12.6 Research Application: Forest Land Protection -- 12.7 Summary -- 12.8 Exercises -- Chapter 13: Dynamic Programming -- 13.1 A Network Problem -- 13.2 Characteristics of Dynamic Programming Problems -- 13.3 A Production Inventory Problem -- 13.4 A Capital Budgeting Problem -- 13.5 Comments on DP -- 13.6 Research Application: Animal Health in Developing Countries -- 13.7 Research Application: Conversion to Organic Arable Farming -- 13.8 Summary -- 13.9 Exercises.

"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"--