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Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling - Couverture souple

Bär, Schirin

 
9783658391782: Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling
Couverture souple
ISBN 10 : 3658391782 ISBN 13 : 9783658391782
Editeur : Springer Vieweg, 2022

Synopsis

The production control of flexible manufacturing systems is a relevant component that must go along with the requirements of being flexible in terms of new product variants, new machine skills and reaction to unforeseen events during runtime. This work focuses on developing a reactive job-shop scheduling system for flexible and re-configurable manufacturing systems. Reinforcement Learning approaches are therefore investigated for the concept of multiple agents that control products including transportation and resource allocation.

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À propos de l'auteur


About the authorSchirin Bär researched at the RWTH-Aachen University at the Institute for Information Management in Mechanical Engineering (IMA) on the optimization of production control of flexible manufacturing systems using reinforcement learning. As operations manager and previously as an engineer, she developed and evaluated the research results based on real systems.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Springer Vieweg
Date d'édition
2022
Langue
anglais
ISBN 10 
3658391782
ISBN 13 
9783658391782
Reliure
Broché
Numéro d'édition
1
Nombre de pages
172
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