1999
DOI: 10.1002/(sici)1099-1425(199905/06)2:3<135::aid-jos21>3.0.co;2-l
|Get access via publisher |Summarize |Cite
Multistage hybrid flowshop scheduling with identical jobs and uniform parallel machines
Search citation statements
Paper Sections
Select...
16
1
0
0
Citation Types
0
5
0
0
Year Published
2004
2017
Publication Types
Select...
13
3
1
Relationship
0
17
Authors
Journals
Cited by 17 publications
(5 citation statements)
References 12 publications
0
5
0
0
“…The hybridization of flow shop and job shop/ Parallel Machines natures to enhance the flexibility of mass production environment incarnates flexible flow shop or Hybrid flow shop. The parallel machines nature like identical [16], uniform [17] and unrelated [18] parallel machines natures are the additional constraints in the flexible flow shop problem.…”
mentioning
confidence: 99%
“…The hybridization of flow shop and job shop/ Parallel Machines natures to enhance the flexibility of mass production environment incarnates flexible flow shop or Hybrid flow shop. The parallel machines nature like identical [16], uniform [17] and unrelated [18] parallel machines natures are the additional constraints in the flexible flow shop problem.…”
mentioning
confidence: 99%
“…The m-stage problem with the weighted tardiness objective was approached by [106] using dispatching rules. [203] study an m-stage problem with uniform parallel machines and identical jobs. They investigate the performance of dispatching rules, some tailored heuristics, and derive lower bounds.…”
Section: Heuristics
mentioning
confidence: 99%
“…For instance Sriskandarajah and Sethi [14] presented heuristic algorithms based on dispatching rules for a flexible flowshop problem with the minimum makespan criterion. Verma and Dessouky [15] studied a multistage problem with identical jobs and uniform parallel machines to minimize the makespan and investigated the performance of dispatching rules. In further study, researchers have developed prominent strategies to enhance the performance of heuristics, known as metaheuristic algorithms.…”
Section: Introduction
mentioning
confidence: 99%
