AMPL : a modeling language for mathematical programming

AMPL is a language for large-scale optimization and mathematical programming problems in production, distribution, blending, scheduling, and many other applications. Combining familiar algebraic notation and a powerful interactive command environment, AMPL makes it easy to create models, use a wide variety of solvers, and examine solutions. Though flexible and convenient for rapid prototyping and development of models, AMPL also offers the speed and generality needed for repeated large-scale production runs. This book, written by the creators of AMPL, is a complete guide for modelers at all levels of experience. It begins with a tutorial on widely used linear programming models, and presents all of AMPL's features for linear programming with extensive examples. Additional chapters cover network, nonlinear, piecewise-linear, and integer programming; database and spreadsheet interactions; and command scripts. Most chapters include exercises. Download free versions of AMPL and several solvers from (http://www.ampl.com) www.ampl.com for experimentation, evaluation, and education. The Web site also lists vendors of the commercial version of AMPL and numerous solvers. Introduction -- 1. Production Models -- 2. Diet And Other Input Models -- 3. Transportation And Assignment Models -- 4. Building Larger Models -- 5. Simple Sets And Indexing -- 6. Compound Sets And Indexing -- 7. Parameters And Expressions -- 8. Linear Programs -- 9. Specifying Data -- 10. Database Access -- 11. Modeling Commands -- 12. Display Commands -- 13. Command Scripts -- 14. Interaction With Solvers -- 15. Network Linear Programs -- 16. Columnwise Formulations -- 17. Piecewise-linear Programs -- 18. Nonlinear Programs -- 19. Complementarity Programs -- 20. Integer Linear Programs -- Appendix -- Index. Robert Fourer, David M. Gay, Brian W. Kernighan. A supplemental textbook introducing mathematical programming using the commercial software package, designed to be used in conjunction with a full text explaining the optimization theory and algorithmic details used in mathematical programming. The second edition incorporates developments in the software since 1992. Annotation copyrighted by Book News, Inc., Portland, OR