Synopses & Reviews
AMPL, developed at AT&Ts Bell Laboratories, is a powerful, yet easy-to-use modeling environment for problems in linear, nonlinear, network, and integer programming. Users can formulate optimization models and analyze solutions using common algebraic notation; the computer manages the interface to advanced optimizers. In less advanced programming software, students must write out every variable and constraint explicitly. AMPLs powerful display commands encourage creative responses to modeling assignments..The AMPL Student Edition is a full-featured version of the AMPL and optimizer software that accepts problems up to 300 variables and 300 constraints. AMPLs modeling approach can handle real-world problems. AMPL student models easily scale up to optimization problems of realistic size. AMPL Student Edition comes with both the MINOS and CPLEX solvers. Beginners need only type solve to invoke an optimizer, but advanced students have full access to algorithmic options because the AMPL Student Edition works just like the professional editions that run on computers from PCs to Crays. Classroom skills transfer directly to the job environment.
Synopsis
AMPL, developed at AT&Ts Bell Laboratories, is a powerful, yet easy-to-use modeling environment for problems in linear, nonlinear, network, and integer programming. Users can formulate optimization models and analyze solutions using common algebraic notation; the computer manages the interface to advanced optimizers. In less advanced programming software, students must write out every variable and constraint explicitly. AMPLs powerful display commands encourage creative responses to modeling assignments..The AMPL Student Edition is a full-featured version of the AMPL and optimizer software that accepts problems up to 300 variables and 300 constraints. AMPLs modeling approach can handle real-world problems. AMPL student models easily scale up to optimization problems of realistic size. AMPL Student Edition comes with both the MINOS and CPLEX solvers. Beginners need only type solve to invoke an optimizer, but advanced students have full access to algorithmic options because the AMPL Student Edition works just like the professional editions that run on computers from PCs to Crays. Classroom skills transfer directly to the job environment.
About the Author
Robert Fourer received his Ph.D. in operations research from Stanford University in 1980 and is an active researcher in mathematical programming and modeling language design. He joined the Department of Industrial Engineering and Management Sciences at Northwestern University in 1979 and served as chair of the department from 1989 to 1995. David M. Gay received his Ph.D. in computer science from Cornell University in 1975, and was in the Computing Science Research Center at Bell Laboratories from 1981 to 2001. He is now CEO of AMPL Optimization LLC. His research interests include numerical analysis, optimization, and scientific computing. Brian Kernighan received his Ph.D. in electrical engineering from Princeton University in 1969. He was in the Computing Science Research Center at Bell Laboratories from 1969 to 2000 and now teaches in the Computer Science department at Princeton. He is the co-author of several computer science books, including THE C PROGRAMMING LANGUAGE and THE UNIX PROGRAMMING ENVIRONMENT.
Table of Contents
1. Production Models: Maximizing Profits. 2. Diets, Blending, and Scheduling: Minimizing Costs. 3. Transportation, Assignment, and Minimum-Cost Flows. 4. Building Larger Models. 5. Simple Sets and Indexing. 6. Compound Sets and Indexing. 7. Parameters and Expressions. 7.7 Syntax Summary. 8. Linear Programs: Variables, Objectives, and Constraints. 9. Specifying Data. 10. Command Environment. 11. Network Linear Programs. 12. Columnwise Formulations. 13. Nonlinear Programs. 14. Piecewise-Linear Programs. 15. Integer Linear Programs. Appendix A: AMPL Reference Manual. Index.