Pivot, Cut, and Dive: a heuristic for 0-1 mixed integer programming

被引：18
|
作者：
Eckstein, Jonathan
Nediak, Mikhail
机构：
[1] Queens Univ, Queens Sch Business, Kingston, ON K7L 3N6, Canada
[2] Rutgers State Univ, RUTCOR, Sch Business, Piscataway, NJ 08854 USA
来源：
JOURNAL OF HEURISTICS | 2007年 / 13卷 / 05期
关键词：
integer programming; simplex pivot; convexity cut;
D O I：
10.1007/s10732-007-9021-7
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes a heuristic for 0- 1 mixed-integer linear programming problems, focusing on "stand-alone" implementation. Our approach is built around concave "merit functions" measuring solution integrality, and consists of four layers: gradient-based pivoting, probing pivoting, convexity/intersection cutting, and diving on blocks of variables. The concavity of the merit function plays an important role in the first and third layers, as well as in connecting the four layers. We present both the mathematical and software details of a test implementation, along with computational results for several variants.
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页码：471 / 503
页数：33
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