Selecting meta-heuristics for solving vehicle routing problems with time windows via meta-learning

作者：

Highlights：

• A new method to solve vehicle routing through meta-learning techniques.

• Two sets of meta-features are used: basic and landmarking meta-features.

• A multilayer perceptron classifier is used to select meta-heuristics.

• Our proposal statistically improves the overall performances previously reported.

摘要

•A new method to solve vehicle routing through meta-learning techniques.•Two sets of meta-features are used: basic and landmarking meta-features.•A multilayer perceptron classifier is used to select meta-heuristics.•Our proposal statistically improves the overall performances previously reported.

论文关键词：Meta-learning,Meta-heuristic,Vehicle routing problems,Time windows

论文评审过程：Received 19 June 2018, Revised 27 September 2018, Accepted 16 October 2018, Available online 17 October 2018, Version of Record 22 October 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.10.036