Abstract
In the vehicle routing problem with simultaneous pickup and delivery (VRPSPD), customers demanding both delivery and pickup operations have to be visited once by a single vehicle. In this work, we propose a fast randomized algorithm using a nearest neighbor strategy to tackle an extension of the VRPSPD in which the fleet of vehicles is heterogeneous. This variant is an NP-hard problem, which in practice makes it impossible to be solved to proven optimality for large instances. To evaluate the proposal, we use benchmark instances from the literature and compare our results to those obtained by a state-of-the-art algorithm. Our approach presents very competitive results, not only improving several of the known solutions, but also running in a shorter time.
Highlights
The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) [1,2,3,4,5,6,7,8,9], in which customers demanding both delivery and pickup operations have to be visited once by a single vehicle, is one of the main classes of the vehicle routing problem (VRP)
We propose a fast randomized algorithm using a nearest neighbor strategy to tackle the HVRPSPD
We present the results obtained by the adaptive hybrid local search (HLS) of Avci and Topaloglu [13]
Summary
The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) [1,2,3,4,5,6,7,8,9], in which customers demanding both delivery and pickup operations have to be visited once by a single vehicle, is one of the main classes of the vehicle routing problem (VRP). This class has attracted research attention due to its applicability in numerous reverse logistic systems. The heterogeneous vehicle routing problem with simultaneous pickup and delivery (HVRPSPD) has received research interest only in very recent years [10,11,12,13]
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