FORMULATING A MIXED-INTEGER PROGRAMMING PROBLEM TO IMPROVE SOLVABILITY
成果类型：
Article
署名作者：
BARNHART, C; JOHNSON, EL; NEMHAUSER, GL; SIGISMONDI, G; VANCE, P
署名单位：
University System of Georgia; Georgia Institute of Technology; University System of Georgia; Georgia Institute of Technology; Auburn University System; Auburn University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.41.6.1013
发表日期：
1993
页码：
1013-1019
关键词：
摘要：
A standard formulation of a real-world distribution problem could not be solved, even for a good solution, by a commercial mixed integer programming code. However, after reformulating it by reducing the number of 0-1 variables and tightening the linear programming relaxation, an optimal solution could be found efficiently. The purpose of this paper is to demonstrate, with a real application, the practical importance of the need for good formulations in solving mixed integer programming problems.