Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling - Paperback
$89.08
Skip to product information
Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling - Paperback
$89.08
by Schirin Bär (Author)
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.
Back Jacket
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.
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.
Author Biography
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.
Number of Pages: 148
Dimensions: 0.37 x 8.27 x 5.83 IN
Illustrated: Yes
Publication Date: October 02, 2022
Details
This product is crafted with quality materials to ensure durability and performance. Designed with your convenience in mind, it seamlessly fits into your everyday life.
Shipping & Returns
We strive to process and ship all orders in a timely manner, working diligently to ensure that your items are on their way to you as soon as possible.
We are committed to ensuring a positive shopping experience for all our customers. If for any reason you wish to return an item, we invite you to reach out to our team for assistance, and we will evaluate every return request with care and consideration.
