A large neighbourhood based heuristic for two-echelon routing problems

TL;DR

This paper introduces a hybrid metaheuristic for two-echelon routing problems in city logistics, achieving state-of-the-art solutions efficiently and providing a unified benchmark dataset for future research.

Contribution

It presents a novel hybrid metaheuristic combining local search and destroy-repair techniques, improving solution quality for two-echelon routing problems.

Findings

Achieves best known solutions for 95% of benchmark instances.

Provides a unified, corrected set of benchmark instances online.

Delivers high-quality solutions with short computation times.

Abstract

In this paper, we address two optimisation problems arising in the context of city logistics and two-level transportation systems. The two-echelon vehicle routing problem and the two-echelon location routing problem seek to produce vehicle itineraries to deliver goods to customers, with transits through intermediate facilities. To efficiently solve these problems, we propose a hybrid metaheuristic which combines enumerative local searches with destroy-and-repair principles, as well as some tailored operators to optimise the selections of intermediate facilities. We conduct extensive computational experiments to investigate the contribution of these operators to the search performance, and measure the performance of the method on both problem classes. The proposed algorithm finds the current best known solutions, or better ones, for 95% of the two-echelon vehicle routing problem benchmark instances. Overall, for both problems, it achieves high-quality solutions within short computing times. Finally, for future reference, we resolve inconsistencies between different versions of benchmark instances, document their differences, and provide them all online in a unified format.