Summary: 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 ...show more 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 www.ampl.com for experimentation, evaluation, and education. The Web site also lists vendors of the commercial version of AMPL and numerous solvers.Edition/Copyright: 2ND 03
- The authors teach the basics of linear programming and optimization in a practical setting.
- The book covers all major kinds of optimization problems through numerous examples.
- Exercises accompany most chapters.
- NEW! Offers coverage of AMPL features added over the past 10 years, whose descriptions were previously only available in rough form on the AMPL web site.
- NEW! Includes new chapters on Database Access, Modeling Commands, Display Commands, Command Scripts, Interactions with Solvers, and Complementarily Problems.
- NEW! Contains an updated Reference Manual in an appendix.
- NEW! Up-to-date student-edition software available for download at http://www.ampl.com.
- The AMPL modeling language was created by the authors of the book, who continue to maintain and enhance it. The language, based on the sort of algebraic notation that is familiar to any mathematics, science or engineering student, lets people describe optimization problems to computers in much the same way that they would describe these problems to other people. It makes it possible to emphasize the kinds of general models that can be used to describe large-scale optimization problems.
Publisher: Brooks/Cole Publishing Co.