论文标题
学习解决车辆路线问题：调查
Learning to Solve Vehicle Routing Problems: A Survey
论文作者
论文摘要
本文提供了针对解决NP固定车辆路由问题（VRP）的机器学习方法的系统概述。最近，机器学习和运营研究社区都引起了人们的极大兴趣，可以通过纯学习方法或将它们与传统的手工启发式方法结合在一起。我们介绍了学习范式，解决方案结构，基础模型和算法的研究分类法。我们详细介绍了最先进的方法的结果，证明了它们使用传统方法的竞争力。该论文概述了未来的研究指示，以结合基于学习的解决方案，以克服现代运输系统的挑战。
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 machine learning and operations research communities to solve VRPs either by pure learning methods or by combining them with the traditional hand-crafted heuristics. We present the taxonomy of the studies for learning paradigms, solution structures, underlying models, and algorithms. We present in detail the results of the state-of-the-art methods demonstrating their competitiveness with the traditional methods. The paper outlines the future research directions to incorporate learning-based solutions to overcome the challenges of modern transportation systems.
