7 citations · 9 across the 4 of their papers we have counts for
4 papers
Deep Reinforcement Learning for Multi-Truck Vehicle Routing Problems with Multi-Leg Demand Routes
Joshua Levin, Randall Correll, Takanori Ide +3
Deep reinforcement learning (RL) has been shown to be effective in producing approximate solutions to some vehicle routing problems (VRPs), especially when using policies generated…
Extended Quantum Spin Liquid with Spinon-like Excitations in an Anisotropic Kitaev-Gamma Model
Matthias Gohlke, Jose Carlos Pelayo, Takafumi Suzuki
The characterization of quantum spin liquid phases in Kitaev materials has been a subject of intensive studies over the recent years, both theoretically and experimentally. Most th…
Quantum Neural Networks for a Supply Chain Logistics Application
Randall Correll, Sean J. Weinberg, Fabio Sanches +2
Problem instances of a size suitable for practical applications are not likely to be addressed during the noisy intermediate-scale quantum (NISQ) period with (almost) pure quantum…
Reinforcement Learning for Multi-Truck Vehicle Routing Problems
Joshua Levin, Randall Correll, Takanori Ide +3
Deep reinforcement learning (RL) has been shown to be effective in producing approximate solutions to some vehicle routing problems (VRPs), especially when using policies generated…