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A Fast Randomized Algorithm for the Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery

Graduate Program in Applied Informatics, University of Fortaleza, 60811-905 Fortaleza, Ceará, Brazil
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Algorithms 2019, 12(8), 158; https://doi.org/10.3390/a12080158
Received: 19 June 2019 / Revised: 31 July 2019 / Accepted: 1 August 2019 / Published: 3 August 2019
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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. View Full-Text
Keywords: vehicle routing problem; greedy algorithms; randomized algorithms vehicle routing problem; greedy algorithms; randomized algorithms
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Nepomuceno, N.; Barboza Saboia, R.; Rogério Pinheiro, P. A Fast Randomized Algorithm for the Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery. Algorithms 2019, 12, 158.

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