Flexible Assembly Job-Shop Scheduling With Sequence-Dependent Setup Times and Part Sharing in a Dynamic Environment: Constraint Programming Model, Mixed-Integer Programming Model, and Dispatching Rules

This paper studies the flexible assembly job-shop scheduling problem in a dynamic manufacturing environment, which is an exension of job-shop scheduling with incorporation of serveral types of flexibilies and integration of an assembly stage. Each product is assembled from several parts with nonline...

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Vydané v:IEEE transactions on engineering management Ročník 65; číslo 3; s. 487 - 504
Hlavní autori: Zhang, Sicheng, Wang, Shouyang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.08.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Assembly
Assembly job-shop scheduling
Completion time
Constraint modelling
constraint programming (CP)
Dispatching
Dispatching rules
Dynamic programming
Dynamic scheduling
Fitness
flexible job-shop scheduling
Genetic algorithms
Integer programming
Job shop scheduling
Job shops
Linear programming
Machining
mixed-integer linear programming (MILP)
Production scheduling
Rescheduling
Scheduling
Sequential scheduling
Setup times
ISSN:0018-9391, 1558-0040
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Shrnutí:This paper studies the flexible assembly job-shop scheduling problem in a dynamic manufacturing environment, which is an exension of job-shop scheduling with incorporation of serveral types of flexibilies and integration of an assembly stage. Each product is assembled from several parts with nonlinear process plans with operations involving alternative machines. Setup times are sequence dependent and serparately considered from processing times. Part sharing is fully allowed such that they can be used for the assembly of any possible product, rather than being preassociated to a specfic product. We employ constraint programming and mixed-integer linear programming to formulate the problem. Besides, several dispatching rules with machine feedback machanism are developped. Experimental studies are conducted based on test case problems with different scales and complexities. It is found that constraint programming is the most efficacious approach, whose solution fitness outperforms mixed-integer linear programming as well as all dispatching rules in both static and dynamic cases. On the other hand, dispatching rules are simple to implement, among which the "earliest completion time" rule is the most favourable. A real-time scheduling/rescheduling system has been constructed for the implementation of the proposed approaches to solve practical problems in production.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0018-9391
1558-0040
DOI:10.1109/TEM.2017.2785774