A constraint generation approach for two-machine shop problems with jobs selection

被引：7
|
作者：
Della Croce, Federico [1 ,2 ]
Koulamas, Christos [3 ]
T'kindt, Vincent [4 ]
机构：
[1] Politecn Torino, DAI, Turin, Italy
[2] CNR, IEIIT, Turin, Italy
[3] Florida Int Univ, Coll Business, Miami, FL 33199 USA
[4] Univ Tours, CNRS, LI EA 6300, OC ERL 6305, Tours, France
来源：
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2017年 / 259卷 / 03期
关键词：
Scheduling; Jobs selection; Two-machine shop problems; Constraint generation approach; SCHEDULING PROBLEM; FLOWSHOP;
D O I：
10.1016/j.ejor.2016.11.036
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
We consider job selection problems in two-stage flow shops and job shops. The aim is to select the best job subset with a given cardinality to minimize the makespan. These problems are known to be ordinary NP-hard and the current state of the art algorithms can solve flow shop problems with up to 3000 jobs. We introduce a constraint generation approach to the integer linear programming (ILP) formulation of these problems according to which the constraints associated with nearly all potential critical paths are relaxed and then only the ones violated by the relaxed solution are sequentially reinstated. The proposed approach is capable of solving problems with up to 100000 jobs. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：898 / 905
页数：8
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