2 citations · 2 across the 7 of their papers we have counts for
8 papers
Improving After-sales Service: Deep Reinforcement Learning for Dynamic Time Slot Assignment with Commitments and Customer Preferences
Xiao Mao, Albert H. Schrotenboer, Guohua Wu +1
Problem definition: For original equipment manufacturers (OEMs), high-tech maintenance is a strategic component in after-sales services, involving close coordination between custom…
A Universal Approach to Feature Representation in Dynamic Task Assignment Problems
Riccardo Lo Bianco, Remco Dijkman, Wim Nuijten +1
Dynamic task assignment concerns the optimal assignment of resources to tasks in a business process. Recently, Deep Reinforcement Learning (DRL) has been proposed as the state of t…
GymPN: A Library for Decision-Making in Process Management Systems
Riccardo Lo Bianco, Willem van Jaarsveld, Remco Dijkman
Process management systems support key decisions about the way work is allocated in organizations. This includes decisions on which task to perform next, when to execute the task,…
Automated decision-making for dynamic task assignment at scale
Riccardo Lo Bianco, Willem van Jaarsveld, Jeroen Middelhuis +2
The Dynamic Task Assignment Problem (DTAP) concerns matching resources to tasks in real time while minimizing some objectives, like resource costs or task cycle time. In this work,…
Classical and Deep Reinforcement Learning Inventory Control Policies for Pharmaceutical Supply Chains with Perishability and Non-Stationarity
Francesco Stranieri, Chaaben Kouki, Willem van Jaarsveld +1
We study inventory control policies for pharmaceutical supply chains, addressing challenges such as perishability, yield uncertainty, and non-stationary demand, combined with batch…
Integrated trucks assignment and scheduling problem with mixed service mode docks: A Q-learning based adaptive large neighborhood search algorithm
Yueyi Li, Mehrdad Mohammadi, Xiaodong Zhang +2
Mixed service mode docks enhance efficiency by flexibly handling both loading and unloading trucks in warehouses. However, existing research often predetermines the number and loca…
Maintenance Optimization for Asset Networks with Unknown Degradation Parameters
Peter Verleijsdonk, Collin Drent, Stella Kapodistria +1
We consider the key practical challenge of multi-asset maintenance optimization in settings where degradation parameters are heterogeneous and unknown, and must be inferred from de…
Contingent Penalty and Contingent Renewal Supply Contracts in High-Tech Industry
Mirjam S Meijer, Willem van Jaarsveld, Ton de Kok +1
Unlike consumer goods industry, a high-tech manufacturer (OEM) often amortizes new product development costs over multiple generations, where demand for each generation is based on…