Adaptive Large Neighborhood Search for Vehicle Routing Problems with Transshipment Facilities Arising in City Logistics
Christian Friedrich, Ralf Elbert

TL;DR
This paper introduces an adaptive large neighborhood search algorithm for vehicle routing problems with transshipment facilities in city logistics, improving solution quality and providing managerial insights.
Contribution
It develops a novel adaptive large neighborhood search method incorporating transshipment options, addressing complex city logistics routing problems with new procedures.
Findings
The method outperforms existing algorithms on benchmark instances.
Transshipment facilities significantly impact routing efficiency.
Managerial insights on fees, order size, and fleet heterogeneity are provided.
Abstract
In this paper, we investigate vehicle routing problems with third-party transshipment facilities that arise in the context of city logistics. Contrary to classical vehicle routing problems, where each customer request is delivered directly to its destination, the problems considered in this paper feature the alternative possibility of delivering customer requests to third-party transshipment facilities, such as urban consolidation centers, for a fee. We present an adaptive large neighborhood search with an embedded random variable neighborhood descent as a local search component and a set-partitioning problem for the recombination of routes to solve various versions of the problem. Thereby, we consider location-dependent time windows as well as heterogeneous fleets and propose several new procedures that consider transshipment facilities within the components of our adaptive large…
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