A Taxonomy for the Flexible Job Shop Scheduling Problem

被引:6
|
作者
Cinar, Didem [1 ,2 ]
Topcu, Y. Ilker [1 ]
Oliveira, Jose Antonio [3 ]
机构
[1] Istanbul Tech Univ, Dept Ind Engn, TR-34367 Istanbul, Turkey
[2] Univ Florida, Fac Engn, Ctr Appl Optimizat, Gainesville, FL 32611 USA
[3] Univ Minho, Dept Prod & Sistemas, Ctr Algoritmi, P-4710057 Braga, Portugal
关键词
Job shop scheduling; Flexible job shop scheduling; Taxonomy; Review; SWARM OPTIMIZATION ALGORITHM; BEE COLONY ALGORITHM; GENETIC ALGORITHM; TABU SEARCH; MATHEMATICAL-MODELS; HEURISTIC ALGORITHM; DISPATCHING RULES; GRASP ALGORITHM; HYBRID; MAINTENANCE;
D O I
10.1007/978-3-319-18567-5_2
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
This chapter aims at developing a taxonomic framework to classify the studies on the flexible job shop scheduling problem (FJSP). The FJSP is a generalization of the classical job shop scheduling problem (JSP), which is one of the oldest NP-hard problems. Although various solution methodologies have been developed to obtain good solutions in reasonable time for FSJPs with different objective functions and constraints, no study which systematically reviews the FJSP literature has been encountered. In the proposed taxonomy, the type of study, type of problem, objective, methodology, data characteristics, and benchmarking are the main categories. In order to verify the proposed taxonomy, a variety of papers from the literature are classified. Using this classification, several inferences are drawn and gaps in the FJSP literature are specified. With the proposed taxonomy, the aim is to develop a framework for a broad view of the FJSP literature and construct a basis for future studies.
引用
收藏
页码:17 / 37
页数:21
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