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

Éditeur :

Springer Vieweg

Paru le : 2022-10-01

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 sched...
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Description du livre

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.

À propos

Auteur
Schirin Bär
Éditeur
Springer Vieweg
Collection
n.c
Parution
2022-10-01
Pages
148 pages
EAN papier
9783658391782

Auteur(s) du livre


Defaut-Illustration Schirin Bär
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.

Caractéristiques détaillées - droits

EAN PDF
9783658391799
Prix
52,74 €
Nombre pages copiables
1
Nombre pages imprimables
14
Taille du fichier
3174 Ko
Ce livre est accessible aux handicaps informations d'accessibilité
EAN EPUB
9783658391799
Prix
52,74 €
Nombre pages copiables
1
Nombre pages imprimables
14
Taille du fichier
13148 Ko
Ce livre est accessible aux handicaps informations d'accessibilité

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