18 citations · 22 across the 4 of their papers we have counts for
4 papers
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…
Supply Chain Logistics with Quantum and Classical Annealing Algorithms
Sean J. Weinberg, Fabio Sanches, Takanori Ide +2
Noisy intermediate-scale quantum (NISQ) hardware is almost universally incompatible with full-scale optimization problems of practical importance which can have many variables and…
Short Quantum Circuits in Reinforcement Learning Policies for the Vehicle Routing Problem
Fabio Sanches, Sean Weinberg, Takanori Ide +1
Quantum computing and machine learning have potential for symbiosis. However, in addition to the hardware limitations from current devices, there are still basic issues that must b…