A Non-Permutation Flow Shop Manufacturing Cell Scheduling Problem with Part's Sequence Dependent Family Setup Times

被引:9
|
作者
Nikjo, Behzad [1 ]
Zarook, Yaser [1 ]
机构
[1] Mazandaran Univ Sci & Technol, Dept Ind Engn, Babol Sar, Iran
关键词
Family Setup Times; Flow Shop Scheduling; Genetic Algorithms; Manufacturing Cell; Tabu Search;
D O I
10.4018/ijamc.2014100104
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article presents a new mathematical model for a dynamic flow shop manufacturing cell scheduling problem (DFMCSP) with agreeable job release date for each part family where family setup times are dependent on sequence of parts within families. It means this article considers non-permutation schedules for both sequence of families and sequence of parts within families. The objective is minimizing the Makespan (C-max). Since, this problem belongs to NP-Hard class. Therefore, reaching an optimal solution in a reasonable computational time by using exact methods is extremely difficult. Thus, this article proposes meta-heuristic methods such as Genetic Algorithms (GA) and Tabu Search (TS). Finally, the computational results compare efficiency of the proposed algorithms under the performance measures.
引用
收藏
页码:70 / 86
页数:17
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