Title: Vehicle routing problem with drones as an aid for epidemic relief

Authors: Shih-Hao Lu; Marco Fabio Benaglia; Anh-Tu Nguyen; Edgar Rojas Rivera; Jen-Wei Cheng

Addresses: Department of Business Administration, School of Management, National Taiwan University of Science and Technology, Taipei City, Taiwan ' Department of Business Administration, School of Management, National Taiwan University of Science and Technology, Taipei City, Taiwan ' Banking Department, Ho Chi Minh City University of Banking, Ho Chi Minh City, Vietnam ' Department of Business Administration, School of Management, National Taiwan University of Science and Technology, Taipei City, Taiwan ' Department of Business Administration, School of Management, National Taiwan University of Science and Technology, Taipei City, Taiwan

Abstract: In response to epidemics, especially if vaccines and cures are not readily available, governments issue lockdowns and impose social distancing. Under such circumstances, to avoid potentially dangerous person-to-person contacts, drones can replace people in performing functions like delivering supplies, collecting swabs, measuring human body temperatures, etc. This paper introduces a new type of vehicle routing problem with multiple drones for epidemic relief (VRP-mD_ER), defined by a MILP mathematical model solved to near-optimality through the combined application of the 'single-linkage' (S-LINK) algorithm, and a heuristic based on greedy randomised adaptive search procedure (GRASP) and genetic algorithm (GA). The proposed model helps reduce the total service time by 15%-19%, to deliver critical supplies quickly, and make relief operations more efficient and cost-effective by saving up to 59% of variable costs. Additionally, we provide a list of optimal combinations of trucks and drones to minimise delivery time and costs, and a sensitivity analysis.

Keywords: vehicle routing problem with drones; VRP-D; pandemic; genetic algorithm; GRASP; epidemic relief; last mile delivery; humanitarian aid; single-linkage.

DOI: 10.1504/IJSTL.2024.139062

International Journal of Shipping and Transport Logistics, 2024 Vol.18 No.3, pp.249 - 280

Received: 06 Aug 2022
Accepted: 12 Nov 2022
Published online: 11 Jun 2024 *

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