A metaheuristic optimization approach for a real-world stochastic flexible flow shop problem with limited buffer

This work deals with a scheduling problem of a real-world production process in the metal–working industry. The production process can be described as an offline stochastic flexible flow-shop problem with limited buffers. In a first step, we analyze a simplified model and develop a variable neighbor...

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Vydáno v:International journal of production economics Ročník 145; číslo 1; s. 88 - 95
Hlavní autoři: Almeder, Christian, Hartl, Richard F.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.09.2013
Elsevier Sequoia S.A
Témata:
Buffers
Computer simulation
Economics
Flexible flow shop
Heuristic
Job shops
Mathematical models
Metaheuristic
Metalworking industry
Optimization
Optimization techniques
Production planning
Scheduling
State of the art
Stochastic models
Stochastic scheduling
Stochasticity
Studies
Variable neighborhood search
Stochastic scheduling
Metaheuristic
Variable neighborhood search
Flexible flow shop
ISSN:0925-5273, 1873-7579
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Shrnutí:This work deals with a scheduling problem of a real-world production process in the metal–working industry. The production process can be described as an offline stochastic flexible flow-shop problem with limited buffers. In a first step, we analyze a simplified model and develop a variable neighborhood search based solution approach where we use multiple scenarios to evaluate the objective. Second, the solution approach is adapted to a real-world case using a detailed discrete-event simulation to evaluate the production plans. We are able to improve state-of-the-art production plans statistically significant by 3–10%.
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ISSN:0925-5273
1873-7579
DOI:10.1016/j.ijpe.2012.09.014