Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling
Author:   Schirin Bär
Publisher:   Springer Fachmedien Wiesbaden
Edition:   1st ed. 2022
ISBN:  

9783658391782


Pages:   148
Publication Date:   02 October 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling


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Author:   Schirin Bär
Publisher:   Springer Fachmedien Wiesbaden
Imprint:   Springer Vieweg
Edition:   1st ed. 2022
Weight:   0.233kg
ISBN:  

9783658391782


ISBN 10:   3658391782
Pages:   148
Publication Date:   02 October 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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.

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Author Information

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.

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