Web: http://arxiv.org/abs/2205.02453

May 6, 2022, 1:11 a.m. | Aigerim Bogyrbayeva, Meraryslan Meraliyev, Taukekhan Mustakhov, Bissenbay Dauletbayev

cs.LG updates on arXiv.org arxiv.org

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 …

arxiv learning routing survey

More from arxiv.org / cs.LG updates on arXiv.org

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC