# Heuristics for Vehicle Routing Problem: A Survey and Recent Advances

arXiv: https://arxiv.org/abs/2303.04147 · HTML: https://mlsanity.com/paper/2303.04147/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 310 references that are in the map.
- First posted on arXiv 1 Mar 2023.

## Builds on (most cited first, 15 of 15)

- [Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon](https://mlsanity.com/paper/1811.06128/) (2018)
- [Reinforcement Learning for Solving the Vehicle Routing Problem](https://mlsanity.com/paper/1802.04240/) (2018)
- [Learning to Perform Local Rewriting for Combinatorial Optimization](https://mlsanity.com/paper/1810.00337/) (2018)
- [Learning Improvement Heuristics for Solving Routing Problems](https://mlsanity.com/paper/1912.05784/) (2019)
- [Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances](https://mlsanity.com/paper/2012.10658/) (2020)
- [End-to-End Constrained Optimization Learning: A Survey](https://mlsanity.com/paper/2103.16378/) (2021)
- [Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood](https://mlsanity.com/paper/2012.10384/) (2020)
- [Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning](https://mlsanity.com/paper/2004.01608/) (2020)
- [PILS: Exploring high-order neighborhoods by pattern mining and injection](https://mlsanity.com/paper/1912.11462/) (2019)
- [Neural Networks for Local Search and Crossover in Vehicle Routing: A Possible Overkill?](https://mlsanity.com/paper/2210.12075/) (2022)
- [A hybrid adaptive Iterated Local Search with diversification control to the Capacitated Vehicle Routing Problem](https://mlsanity.com/paper/2012.11021/) (2020)
- [AILS-II: An Adaptive Iterated Local Search Heuristic for the Large-scale Capacitated Vehicle Routing Problem](https://mlsanity.com/paper/2205.12082/) (2022)
- [An adaptive data-driven approach to solve real-world vehicle routing problems in logistics](https://mlsanity.com/paper/2001.02094/) (2020)
- [Neuro CROSS exchange: Learning to CROSS exchange to solve realistic vehicle routing problems](https://mlsanity.com/paper/2206.02771/) (2022)
- [A Hybrid Heuristic for a Broad Class of Vehicle Routing Problems with Heterogeneous Fleet](https://mlsanity.com/paper/1803.01930/) (2018)

## Built on by (most cited first, 7 of 7)

- [ARS: Automatic Routing Solver with Large Language Models](https://mlsanity.com/paper/2502.15359/) (2025)
- [Learning to Insert for Constructive Neural Vehicle Routing Solver](https://mlsanity.com/paper/2505.13904/) (2025)
- [ACEvo: Adversarial Co-Evolution of Problem Distributions and Solvers for Combinatorial Optimization](https://mlsanity.com/paper/2506.02594/) (2025)
- [Probing Neural Combinatorial Optimization Models](https://mlsanity.com/paper/2510.22131/) (2025)
- [Game-Theoretic Co-Evolution for LLM-Based Heuristic Discovery](https://mlsanity.com/paper/2601.22896/) (2026)
- [Automated Large-scale CVRP Solver Design via LLM-assisted Flexible MCTS](https://mlsanity.com/paper/2605.03339/) (2026)
- [Dynamic Vehicle Routing Problem with Prompt Confirmation of Advance Requests](https://mlsanity.com/paper/2603.07422/) (2026)

## Abstract (arXiv)

Vehicle routing is a well-known optimization research topic with significant practical importance. Among different approaches to solving vehicle routing, heuristics can produce a satisfactory solution at a reasonable computational cost. Consequently, much effort has been made in the past decades to develop vehicle routing heuristics. In this article, we systematically survey the existing vehicle routing heuristics, particularly on works carried out in recent years. A classification of vehicle routing heuristics is presented, followed by a review of their methodologies, recent developments, and applications. Moreover, we present a general framework of state-of-the-art methods and provide insights into their success. Finally, three emerging research topics with notable works and future directions are discussed.