65 citations · 111 across the 9 of their papers we have counts for
4 papers · 1 filter
Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach
Stephen Mak, Liming Xu, Tim Pearce +2
Collaborative vehicle routing occurs when carriers collaborate through sharing their transportation requests and performing transportation requests on behalf of each other. This ac…
Coalitional Bargaining via Reinforcement Learning: An Application to Collaborative Vehicle Routing
Stephen Mak, Liming Xu, Tim Pearce +2
Collaborative Vehicle Routing is where delivery companies cooperate by sharing their delivery information and performing delivery requests on behalf of each other. This achieves ec…
Using Reinforcement Learning for the Three-Dimensional Loading Capacitated Vehicle Routing Problem
Stefan Schoepf, Stephen Mak, Julian Senoner +3
Heavy goods vehicles are vital backbones of the supply chain delivery system but also contribute significantly to carbon emissions with only 60% loading efficiency in the United Ki…
Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates
Kyle Mana, Fernando Acero, Stephen Mak +4
Discrete optimization belongs to the set of -hard problems, spanning fields such as mixed-integer programming and combinatorial optimization. A current standard appro…