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Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling
Taschenbuch von Schirin Bär
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor
About the author
Schirin 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.
Inhaltsverzeichnis
Introduction.- Requirements for Production Scheduling in Flexible Manufacturing.- Reinforcement Learning as an Approach for Flexible Scheduling.- Concept for Multi-Resources Flexible Job-Shop Scheduling.- Multi-Agent Approach for Reactive Scheduling in Flexible Manufacturing.- Empirical Evaluation of the Requirements.- Integration into a Flexible Manufacturing System.- Bibliography.
Details
Erscheinungsjahr: 2022
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 172
Inhalt: xxii
148 S.
4 s/w Illustr.
35 farbige Illustr.
148 p. 39 illus.
35 illus. in color.
ISBN-13: 9783658391782
ISBN-10: 3658391782
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Bär, Schirin
Auflage: 1st ed. 2022
Hersteller: Springer Fachmedien Wiesbaden
Springer Fachmedien Wiesbaden GmbH
Maße: 210 x 148 x 10 mm
Von/Mit: Schirin Bär
Erscheinungsdatum: 02.10.2022
Gewicht: 0,231 kg
preigu-id: 123329330
Über den Autor
About the author
Schirin 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.
Inhaltsverzeichnis
Introduction.- Requirements for Production Scheduling in Flexible Manufacturing.- Reinforcement Learning as an Approach for Flexible Scheduling.- Concept for Multi-Resources Flexible Job-Shop Scheduling.- Multi-Agent Approach for Reactive Scheduling in Flexible Manufacturing.- Empirical Evaluation of the Requirements.- Integration into a Flexible Manufacturing System.- Bibliography.
Details
Erscheinungsjahr: 2022
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 172
Inhalt: xxii
148 S.
4 s/w Illustr.
35 farbige Illustr.
148 p. 39 illus.
35 illus. in color.
ISBN-13: 9783658391782
ISBN-10: 3658391782
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Bär, Schirin
Auflage: 1st ed. 2022
Hersteller: Springer Fachmedien Wiesbaden
Springer Fachmedien Wiesbaden GmbH
Maße: 210 x 148 x 10 mm
Von/Mit: Schirin Bär
Erscheinungsdatum: 02.10.2022
Gewicht: 0,231 kg
preigu-id: 123329330
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