Integer Programming

A practical, accessible guide to optimization problems with discrete or integer variables Integer Programming stands out from other textbooks by explaining in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems, such as airline timetables, production line schedules, or electricity production on a regional or national scale. Incorporating recent developments that have made it possible to solve difficult optimization problems with greater accuracy, author Laurence A. Wolsey presents a number of state-of-the-art topics not covered in any other textbook. These include improved modeling,cutting plane theory and algorithms, heuristic methods, and branch-and-cut and integer programming decomposition algorithms.This self-contained text: \* Distinguishes between good and bad formulations in integer programming problems \* Applies lessons learned from easy integer programs to more difficult problems \* Demonstrates with applications theoretical and practical aspects of problem solving \* Includes useful notes and end-of-chapter exercises \* Offers tremendous flexibility for tailoring material to different needs Integer Programming is an ideal text for courses in integer/mathematical programming-whether in operations research,mathematics, engineering, or computer science departments. It is also a valuable reference for industrial users of integer programming and researchers who would like to keep up with advances in the field.

A practical, accessible guide to optimization problems with discrete or integer variables

Integer Programming stands out from other textbooks by explaining in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems, such as airline timetables, production line schedules, or electricity production on a regional or national scale.

Incorporating recent developments that have made it possible to solve difficult optimization problems with greater accuracy, author Laurence A. Wolsey presents a number of state-of-the-art topics not covered in any other textbook. These include improved modeling, cutting plane theory and algorithms, heuristic methods, and branch-and-cut and integer programming decomposition algorithms. This self-contained text:

* Distinguishes between good and bad formulations in integer programming problems

* Applies lessons learned from easy integer programs to more difficult problems

* Demonstrates with applications theoretical and practical aspects of problem solving

* Includes useful notes and end-of-chapter exercises

* Offers tremendous flexibility for tailoring material to different needs

Integer Programming is an ideal text for courses in integer/mathematical programming-whether in operations research, mathematics, engineering, or computer science departments. It is also a valuable reference for industrial users of integer programming and researchers who would like to keep up with advances in the field.

Booknews

A textbook for courses in integer/mathematical programming, which explains how to construct algorithms or use existing commercial software to obtain solutions for a variety of real-world problems such as airline timetables or production line schedules. Topics covered include improved modeling, cutting plain theory, heuristic methods, and branch-and-cut and integer programming decomposition algorithms. Annotation c. by Book News, Inc., Portland, Or.

A practical, accessible guide to optimization problems with discrete or integer variables Integer Programming stands out from other textbooks by explaining in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems, such as airline timetables, production line schedules, or electricity production on a regional or national scale. Incorporating recent developments that have made it possible to solve difficult optimization problems with greater accuracy, author Laurence A. Wolsey presents a number of state-of-the-art topics not covered in any other textbook. These include improved modeling, cutting plane theory and algorithms, heuristic methods, and branch-and-cut and integer programming decomposition algorithms. This self-contained text: Integer Programming is an ideal text for courses in integer/mathematical programming-whether in operations research, mathematics, engineering, or computer science departments. It is also a valuable reference for industrial users of integer programming and researchers who would like to keep up with advances in the field. "Integer Programming stands out from other textbooks by explaining in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems such as airline timetables, production line schedules, or electricity production on a regional or national scale." "Integer Programming is an ideal text for courses in integer/mathematical programming - whether in operations research, mathematics engineering, or computer science departments. It is also a valuable reference for industrial users of integer programming and researchers who would like to keep up with advances in the field."--Jacket This volume is aimed at users of integer programming who wish to understand why some problems are difficult to solve, how techniques can be reformulated to give better results, and how mixed integer programming systems can be used more effectively. Written by the co-author (with George Nemhauser) of the very successful Integer and Combinatorial Optimization (ISBN 0-471-82819-X), this book fills a void by providing a comprehensive yet clear guide to this popular area, written at an intermediate level. The text is essentially self-contained, though some familiarity with integer programming is assumed and/or desirable, while a few basic concepts from graph theory are used. Formulations. Optimality, Relaxation, and Bounds. Well-Solved Problems. Matchings and Assignments. Dynamic Programming. Complexity and Problem Reductions. Branch and Bound. Cutting Plane Algorithms. Strong Valid Inequalities. Lagrangian Duality. Column Generation Algorithms. Heuristic Algorithms. From Theory to Solutions.