Fast heuristics for the maximum feasible subsystem problem

被引:58
作者
Chinneck, JW [1 ]
机构
[1] Carleton Univ, Ottawa, ON K1S 5B6, Canada
关键词
linear programming; artificial intelligence; heuristic; analysis of algorithms;
D O I
10.1287/ijoc.13.3.210.12632
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Given an infeasible set of linear constraints, finding the maximum cardinality feasible subsystem is known as the maximum feasible subsystem problem. This problem is known to be NP-hard, but has many practical applications. This paper presents improved heuristics for solving the maximum feasible subsystem problem that are significantly faster than the original, but still highly accurate.
引用
收藏
页码:210 / 223
页数:14
相关论文
共 25 条
[1]   THE COMPLEXITY AND APPROXIMABILITY OF FINDING MAXIMUM FEASIBLE SUBSYSTEMS OF LINEAR RELATIONS [J].
AMALDI, E ;
KANN, V .
THEORETICAL COMPUTER SCIENCE, 1995, 147 (1-2) :181-210
[2]  
Amaldi E, 1999, LECT NOTES COMPUT SC, V1610, P45
[3]  
Amaldi E., 1994, THESIS EPFL
[4]  
[Anonymous], P 13 INT JOINT C ART
[5]  
Bennet K. P., 1997, INFORMS Journal on Computing, V9, P311, DOI 10.1287/ijoc.9.3.311
[6]  
Blake C.L., 1998, UCI repository of machine learning databases
[7]  
Brown G, 1975, ORSA TIMS C
[8]   SOME RESULTS CONCERNING POST-INFEASIBILITY ANALYSIS [J].
CHAKRAVARTI, N .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1994, 73 (01) :139-143
[9]   Hybrid misclassification minimization [J].
Chen, CH ;
Mangasarian, OL .
ADVANCES IN COMPUTATIONAL MATHEMATICS, 1996, 5 (2-3) :127-136
[10]  
CHIN J, 1994, CLIN PERINATOL, V21, P1, DOI 10.1016/0305-0548(94)90057-4