19 citations · 35 across the 5 of their papers we have counts for
5 papers
Deep Reinforcement Learning with Adjustments
Hamed Khorasgani, Haiyan Wang, Chetan Gupta +1
Deep reinforcement learning (RL) algorithms can learn complex policies to optimize agent operation over time. RL algorithms have shown promising results in solving complicated prob…
Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning
Chi Zhang, Philip Odonkor, Shuai Zheng +3
Dynamic dispatching is one of the core problems for operation optimization in traditional industries such as mining, as it is about how to smartly allocate the right resources to t…
Regularized Operating Envelope with Interpretability and Implementability Constraints
Qiyao Wang, Haiyan Wang, Chetan Gupta +1
Operating envelope is an important concept in industrial operations. Accurate identification for operating envelope can be extremely beneficial to stakeholders as it provides a set…
Manufacturing Dispatching using Reinforcement and Transfer Learning
Shuai Zheng, Chetan Gupta, Susumu Serita
Efficient dispatching rule in manufacturing industry is key to ensure product on-time delivery and minimum past-due and inventory cost. Manufacturing, especially in the developed w…
Remaining Useful Life Estimation Using Functional Data Analysis
Qiyao Wang, Shuai Zheng, Ahmed Farahat +2
Remaining Useful Life (RUL) of an equipment or one of its components is defined as the time left until the equipment or component reaches its end of useful life. Accurate RUL estim…