Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness

被引:10
作者
Sueer, Guersel A. [1 ]
Ates, Ozan K. [1 ]
Mese, Emre M. [1 ]
机构
[1] Ohio Univ, Russ Coll Engn & Technol, Ind & Syst Engn Dept, Athens, OH 45701 USA
关键词
cell scheduling; group scheduling; genetic algorithms; mixed integer linear programming; heuristics; ALGORITHMS;
D O I
10.1080/00207543.2014.903343
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60-100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper.
引用
收藏
页码:5656 / 5674
页数:19
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