reinforcement learning

Gamifying the vehicle routing problem with stochastic requests

Do you remember your first video game console? We remember ours. Decades ago, they provided hours of entertainment. Now, we have repurposed them to solve dynamic and stochastic optimization problems. With deep reinforcement learning methods posting …

Solving multi-echelon inventory problems using deep reinforcement learning with centralized control (CORS)

A technical talk on the use of reinforcement learning for inventory management.

Dynamic ride-hailing with electric vehicles

We consider the problem of an operator controlling a fleet of electric vehicles for use in a ride-hailing service. The operator, seeking to maximize profit, must assign vehicles to requests as they arise as well as recharge and reposition vehicles in …

Solving multi-echelon inventory problems with heuristic-guided deep reinforcement learning and centralized control (CORS)

A technical talk on reinforcement learning for inventory control.

Solving multi-echelon inventory problems with heuristic-guided deep reinforcement learning and centralized control (JOPT)

A technical talk on reinforcement learning for inventory control.

Integration of machine learning and operations research to solve more realistic problems (CIRRELT)

An overview talk of past and current research.

Solving multi-echelon inventory problems with heuristic-guided deep reinforcement learning and centralized control

Multi-echelon inventory models aim to minimize the system-wide total cost in a multi-stage supply chain by applying a proper ordering policy to each of the stages. In a practical inventory system when backlog costs can be incurred in multiple stages, …