This paper proposes a joint optimization approach for the production decisionmaking and inventory allocation in a fault-prone machine supply chain system, considering production and supply uncertainty as well as the impact of machine failure. A model based on Markov decision theory is presented...

In the era of Industry 4.0, order scheduling is a crucial link in the production of manufacturing enterprises. In view of order scheduling in manufacturing enterprises, a finite horizon MDP (Markov decision process) model is proposed in this work based on two sets of equipment and three types of...

We study the dynamic ambulance dispatch problem in emergency medical services, in which a decision-maker sequentially observes call arrivals and decides which unit to dispatch to service the call, where the service times follow independent and heterogeneous distributions for each...

Stochastic gradient descent (SGD) has proven effective in solving many inventory control problems with demand learning. However, it often faces the pitfall of an infeasible target inventory level that is lower than the current inventory level. Several recent works (e.g., (Huh and...

Robust revenue management has received much interest from both academics and practitioners alike. But the airlines have not embraced it for its current inadequacy to address the practical needs for both fine control of conservatism and the adaptability to changing environments. The single-leg...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all...