The vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem,
and many models and algorithms have been proposed to solve the VRP and its variants …

We present NeuroLKH, a novel algorithm that combines deep learning with the strong
traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem …

Routing problems are a class of combinatorial problems with many practical applications.
Recently, end-to-end deep learning methods have been proposed to learn approximate …

Recently numerous machine learning based methods for combinatorial optimization
problems have been proposed that learn to construct solutions in a sequential decision …

Large-scale Vehicle Routing Problems (VRPs) are widely used in logistics, transportation,
supply chain, and robotic systems. Recently, data-driven VRP heuristics are proposed to …

Abstract The Orienteering Problem with Time Windows (OPTW) is a combinatorial
optimization problem where the goal is to maximize the total score collected from different …

This paper provides a systematic overview of machine learning methods applied to solve NP-
hard Vehicle Routing Problems (VRPs). Recently, there has been a great interest from both …

Although several surveys on Neural Combinatorial Optimization (NCO) solvers specifically
designed to solve Vehicle Routing Problems (VRPs) have been conducted. These existing …

This paper provides a systematic overview of machine learning methods applied to solve NP-
hard Vehicle Routing Problems (VRPs). Recently, there has been great interest from both …

Deploying Unmanned Aerial Vehicles (UAVs) for traffic monitoring has been a hotspot given
their flexibility and broader view. However, a UAV is usually constrained by battery capacity …