5 citations · 12 across the 6 of their papers we have counts for
3 papers · 1 filter
Sample-Efficient, Exploration-Based Policy Optimisation for Routing Problems
Nasrin Sultana, Jeffrey Chan, Tabinda Sarwar +1
Model-free deep-reinforcement-based learning algorithms have been applied to a range of COPs~\cite{bello2016neural}~\cite{kool2018attention}~\cite{nazari2018reinforcement}. However…
Learning Vehicle Routing Problems using Policy Optimisation
Nasrin Sultana, Jeffrey Chan, A. K. Qin +1
Deep reinforcement learning (DRL) has been used to learn effective heuristics for solving complex combinatorial optimisation problem via policy networks and have demonstrated promi…
Learning to Optimise General TSP Instances
Nasrin Sultana, Jeffrey Chan, A. K. Qin +1
The Travelling Salesman Problem (TSP) is a classical combinatorial optimisation problem. Deep learning has been successfully extended to meta-learning, where previous solving effor…