4 papers · 1 filter
Learning to recover: Adaptive local branching with reinforcement learning for log-truck routing and scheduling under disruptions
Abdelhakim Abdellaoui, Issmail El Hallaoui, Loubna Benabbou +2
We consider the real-time reoptimisation of log-truck routing and scheduling in the Canadian forestry industry following unforeseen disruptions. Road closures, vehicle breakdowns,…
Real-World, Large Scale, Multi-Period Log Truck Routing and Scheduling : Application to Canadian Forestry
Abdelhakim Abdellaoui, Issmail El Hallaoui, Loubna Benabbou +2
This paper addresses the multi-period log-truck routing and scheduling problem (), a key operational activity in the forestry industry, where transportation accoun…
Learning Implicit Feasibility Constraints for Real-World Routing and Scheduling: Application to Log Transportation
Abdelhakim Abdellaoui, Ayoub Boufous, Issmail El Hallaoui +3
Real-world vehicle routing and scheduling problems involve complex operational rules and feasibility constraints typically formulated as mixed-integer linear programs (MILP). Howev…
Towards a connection between the capacitated vehicle routing problem and the constrained centroid-based clustering
Abdelhakim Abdellaoui, Loubna Benabbou, Issmail El Hallaoui
Efficiently solving a vehicle routing problem (VRP) in a practical runtime is a critical challenge for delivery management companies. This paper explores both a theoretical and exp…