Learning to Solve Vehicle Routing Problems: A Survey

• URL: http://arxiv.org/abs/2205.02453v1
• Date: Thu, 5 May 2022 05:48:16 GMT
• Title: Learning to Solve Vehicle Routing Problems: A Survey
• Authors: Aigerim Bogyrbayeva, Meraryslan Meraliyev, Taukekhan Mustakhov, Bissenbay Dauletbayev
• Abstract summary: We present the taxonomy of the studies for learning paradigms, solution structures, underlying models, and algorithms. The paper outlines the future research directions to incorporate learning-based solutions to overcome the challenges of modern transportation systems.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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