Modeling and heuristics for scheduling of distributed job shops

被引:92
|
作者
Naderi, B. [1 ,2 ]
Azab, A. [1 ]
机构
[1] Univ Windsor, Fac Engn, Prod Lifecycle Management Res Lab, Dept Ind & Mfg Syst Engn, Windsor, ON N9B 3P4, Canada
[2] Univ Kharazmi, Fac Engn, Dept Ind Engn, Karaj, Iran
基金
加拿大自然科学与工程研究理事会;
关键词
Distributed job shop scheduling; Mathematical modeling; Greedy heuristics; GENETIC ALGORITHM; MINIMIZING MAKESPAN;
D O I
10.1016/j.eswa.2014.06.023
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 deals with the problem of distributed job shop scheduling in which the classical single-facility job shop is extended to the multi-facility one. The mathematical formulation of the problem is comprehensively discussed. Two different mixed integer linear programming models in form of sequence and position based variables are proposed. Using commercial software of CPLEX, the small sized problems are optimally solved. To solve large sized problems, besides adapting three well-known heuristics, three greedy heuristics are developed. The basic idea behind the developed heuristics is to iteratively insert operations (one at each iteration) into a sequence to build up a complete permutation of operations. The permutation scheme, although having several advantages, suffers from redundancy which is having many different permutations representing the same schedule. The issue is analyzed to recognize the redundant permutation. That improves efficiency of heuristics. Comprehensive experiments are conducted to evaluate the performance of the two models and the six heuristics. The results show sequence based model and greedy heuristics equipped with redundancy exclusion are effective for the problem. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7754 / 7763
页数:10
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