71 citations · 76 across the 6 of their papers we have counts for
7 papers
After-sales services during an asset's lifetime: collaborative planning of system upgrades
Fiona Sloothaak, Alp Akçay, Matthieu van der Heijden +1
We consider a physical asset consisting of complex systems, where the systems may require upgrades during the lifetime of the asset. In practice, the asset owner and system supplie…
Policies for the Dynamic Traveling Maintainer Problem with Alerts
Paulo da Costa, Peter Verleijsdonk, Simon Voorberg +4
Downtime of industrial assets such as wind turbines and medical imaging devices comes at a sharp cost. To avoid such downtime costs, companies seek to initiate maintenance just bef…
Biomanufacturing Harvest Optimization with Small Data
Bo Wang, Wei Xie, Tugce Martagan +2
In biopharmaceutical manufacturing, fermentation processes play a critical role in productivity and profit. A fermentation process uses living cells with complex biological mechani…
Algorithms for slate bandits with non-separable reward functions
Jason Rhuggenaath, Alp Akcay, Yingqian Zhang +1
In this paper, we study a slate bandit problem where the function that determines the slate-level reward is non-separable: the optimal value of the function cannot be determined by…
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang +1
Recent works using deep learning to solve the Traveling Salesman Problem (TSP) have focused on learning construction heuristics. Such approaches find TSP solutions of good quality…
Remaining Useful Lifetime Prediction via Deep Domain Adaptation
Paulo R. de O. da Costa, Alp Akcay, Yingqian Zhang +1
In Prognostics and Health Management (PHM) sufficient prior observed degradation data is usually critical for Remaining Useful Lifetime (RUL) prediction. Most previous data-driven…