Ampl: A Modling Language for Mathematical Programming/Book & IBM 31/2 Disk

By David M. Gay, Robert Fourer, Brian W. Kernighan

Book Overview

The is a MS-DOS version 3.2 and compatible with later operating systems such as Microsoft Windows. It can be used with Intel 80386 or a compatible microprocessor with 4 MB of disk space and 2 or more MB of memory. This student edition has a conventional memory variant that can be used on any MS-DOS machine with 640K. Developed at AT&T's Bell Laboratories, AMPL is a modelling environment for problems in linear, non-linear, network and integer programming. Users can formulate optimization models and analyze solutions using common algebraic notation: the computer manages the interface to advanced optimizmers. The package includes a textbook that presents both the fundamentals of optimization modelling and the AMPL modelling language. The book is supported by a full-featured version of the AMPL(under MS-DOS) and optimizer software that accepts problems of up to 300 variables and 300 constants.

• Format: Paperback
• Language: English
• ISBN: 0894262327
• ISBN13: 9780894262326
• Release Date: January 1993
• Publisher: Scientific Pr
• Length: 350 Pages
• Weight: 1.85 lbs.
• Dimensions: 9.8" x 7.8" x 1.0"

Customer Reviews

BEST MODELING LANGUAGE IN THE WORLD

CreativeClearConsistentCost little

A Great Companion for Great Software

Most software "companions" (more than a manual...not quite a book) really do not do justice to the software. Quite the contrary for the AMPL guide. AMPL (the language) is a *very* powerful and *very* easy to use Optimization package. It interfaces with most of the major solvers. Users program in AMPL which is more or less pseudocode and then solve LP, nonlinear, combinatorial, integer, etc. programs. Unlike most software packages, it is both robust and easy to use. Likewise with the companion/book. There are many great, easy to follow examples, and it clearly explains the intrecacies of the language. A must use software and most own book for anyone doing any optimization work.