Identification of Superior Improvement Trajectories for Production Lines via Simulation-Based Optimization with Reinforcement Learning

2021 ◽  
pp. 405-413
Author(s):  
Günther Schuh ◽  
Andreas Gützlaff ◽  
Matthias Schmidhuber ◽  
Jan Maetschke ◽  
Max Barkhausen ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Production Lines ◽  
Simulation Based ◽  
Simulation Based Optimization

scholarly journals A storage expansion planning framework using reinforcement learning and simulation-based optimization

2021 ◽  
Vol 290 ◽  
pp. 116778
Author(s):  
Stamatis Tsianikas ◽  
Nooshin Yousefi ◽  
Jian Zhou ◽  
Mark D. Rodgers ◽  
David Coit
Keyword(s):  
Reinforcement Learning ◽  
Expansion Planning ◽  
Planning Framework ◽  
Simulation Based ◽  
Simulation Based Optimization

Simulation-based optimization of radiotherapy: Agent-based modeling and reinforcement learning

2017 ◽  
Vol 133 ◽  
pp. 235-248 ◽  
Author(s):  
Ammar Jalalimanesh ◽  
Hamidreza Shahabi Haghighi ◽  
Abbas Ahmadi ◽  
Madjid Soltani
Keyword(s):  
Reinforcement Learning ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Simulation Based ◽  
Simulation Based Optimization

Improving configuration of complex production lines via simulation-based optimization

2017 ◽  
Vol 109 ◽  
pp. 295-312 ◽  
Author(s):  
Mustafa Fatih Yegul ◽  
Fatih Safa Erenay ◽  
Soeren Striepe ◽  
Mustafa Yavuz
Keyword(s):  
Production Lines ◽  
Simulation Based ◽  
Simulation Based Optimization

Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning

2019 ◽  
Author(s):  
Zhiwei (Tony) Qin ◽  
Xiaocheng Tang ◽  
Yan Jiao ◽  
Fan Zhang ◽  
Chenxi Wang ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Human Computer Interaction ◽  
Ride Sharing ◽  
Simulation Based ◽  
Computer Interaction

In this demo, we will present a simulation-based human-computer interaction of deep reinforcement learning in action on order dispatching and driver repositioning for ride-sharing.  Specifically, we will demonstrate through several specially designed domains how we use deep reinforcement learning to train agents (drivers) to have longer optimization horizon and to cooperate to achieve higher objective values collectively. 

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