An efficient search method for multi-objective flexible job shop scheduling problems

被引:99
作者
Xing, Li-Ning [1 ]
Chen, Ying-Wu [1 ]
Yang, Ke-Wei [1 ]
机构
[1] Natl Univ Def Technol, Coll Informat Syst & Management, Dept Management Sci & Engn, Changsha 410073, Hunan, Peoples R China
关键词
Combinatorial optimization; Local search; Flexible jobshop scheduling; Multi-objective optimization; Production schedules; HYBRID GENETIC ALGORITHM; SHIFTING BOTTLENECK; TABU SEARCH; OPTIMIZATION; KNOWLEDGE; FRAMEWORK;
D O I
10.1007/s10845-008-0216-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Flexible job shop scheduling is very important in both fields of production management and combinatorial optimization. Owing to the high computational complexity, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches. Motivated by some empirical knowledge, we propose an efficient search method for the multi-objective flexible job shop scheduling problems in this paper. Through the work presented in this work, we hope to move a step closer to the ultimate vision of an automated system for generating optimal or near-optimal production schedules. The final experimental results have shown that the proposed algorithm is a feasible and effective approach for the multi-objective flexible job shop scheduling problems.
引用
收藏
页码:283 / 293
页数:11
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