Search Results for author: Tabinda Sarwar

Found 4 papers, 0 papers with code

Sample-Efficient, Exploration-Based Policy Optimisation for Routing Problems

no code implementations31 May 2022 Nasrin Sultana, Jeffrey Chan, Tabinda Sarwar, A. K. Qin

In this paper, we show that our model can generalise to various route problems, such as the split-delivery VRP (SDVRP), and compare the performance of our method with that of current state-of-the-art approaches.

Efficient Exploration reinforcement-learning +1

Learning Enhanced Optimisation for Routing Problems

no code implementations17 Sep 2021 Nasrin Sultana, Jeffrey Chan, Tabinda Sarwar, Babak Abbasi, A. K. Qin

However, there is still a substantial gap in solution quality between machine learning and operations research algorithms.

BIG-bench Machine Learning

Learning Vehicle Routing Problems using Policy Optimisation

no code implementations24 Dec 2020 Nasrin Sultana, Jeffrey Chan, A. K. Qin, Tabinda Sarwar

In our evaluation, we experimentally illustrate that the model produces state-of-the-art performance on variants of Vehicle Routing problems such as Capacitated Vehicle Routing Problem (CVRP), Multiple Routing with Fixed Fleet Problems (MRPFF) and Travelling Salesman problem.

reinforcement-learning Reinforcement Learning (RL)

Learning to Optimise General TSP Instances

no code implementations23 Oct 2020 Nasrin Sultana, Jeffrey Chan, A. K. Qin, Tabinda Sarwar

In recent years, learning to optimise approaches have shown success in solving TSP problems.

Meta-Learning

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