Multi-agent-based proactive–reactive scheduling for a job shop

Multi-agent-based proactive–reactive scheduling for job shops is presented, aiming to hedge against the uncertainties of dynamic manufacturing environments. This scheduling mechanism consists of two stages, including proactive scheduling stage and reactive scheduling stage. In the proactive scheduli...

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Veröffentlicht in:International journal of advanced manufacturing technology Jg. 59; H. 1-4; S. 311 - 324
Hauptverfasser: Lou, Ping, Liu, Quan, Zhou, Zude, Wang, Huaiqing, Sun, Sherry Xiaoyun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Springer-Verlag 01.03.2012
Springer Nature B.V
Schlagworte:
Algorithms
CAE) and Design
Computer-Aided Engineering (CAD
Engineering
Industrial and Production Engineering
Job shop scheduling
Job shops
Mechanical Engineering
Media Management
Multiagent systems
Original Article
Production scheduling
Schedules
Stochastic models
Uncertainty
Reactive scheduling
Robust scheduling
Proactive scheduling
Multi-agent technology
ISSN:0268-3768, 1433-3015
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Zusammenfassung:Multi-agent-based proactive–reactive scheduling for job shops is presented, aiming to hedge against the uncertainties of dynamic manufacturing environments. This scheduling mechanism consists of two stages, including proactive scheduling stage and reactive scheduling stage. In the proactive scheduling stage, the objective is to generate a robust predictive schedule against known uncertainties; in the reactive scheduling stage, the objective is to dynamically rectify the predictive schedule to adapt to unknown uncertainties, viz. the reactive scheduling stage is actually complementary to the proactive scheduling stage. A stochastic model is presented, which concerns uncertain processing times in proactive scheduling stage on the basis of analyzing the deficiencies of a classical scheduling model for a production schedule in practice. For the stochastic scheduling problem, a multi-agent-based architecture is proposed and a distributed scheduling algorithm is used to solve this stochastic problem. Finally, the repair strategies are introduced to maintain the original proactive schedule when unexpected events occur. Case study examples show that this scheduling mechanism generates more robust schedules than the classical scheduling mechanism.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-011-3482-4