A Multi-Agent Reinforcement Learning Approach to the Dynamic Job Shop Scheduling Problem
A Multi-Agent Reinforcement Learning Approach to the Dynamic Job Shop Scheduling Problem
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
In a production environment, scheduling decides job and machine allocations and the operation sequence. In a job shop production system, the wide variety of jobs, complex routes, and real-life events becomes challenging for scheduling activities. New, unexpected events disrupt the production schedule and require dynamic scheduling updates to the pr...
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Full title
A Multi-Agent Reinforcement Learning Approach to the Dynamic Job Shop Scheduling Problem
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Author / Creator
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TN_cdi_proquest_journals_2819495784
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2819495784
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ISSN
2071-1050
E-ISSN
2071-1050
DOI
10.3390/su15108262
