A Proactive Approach to Extended Vehicle Routing Problem with Drones (EVRPD)

Unmanned aerial vehicles (UAVs), also known as drones, are increasingly common and popular due to their relatively low prices and high mobility. The number of areas for their practical applications is rapidly growing. The most promising are: last-mile delivery, emergency response, the inspection of...

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Vydané v:Applied sciences Ročník 12; číslo 16; s. 8255
Hlavní autori: Sitek, Paweł, Wikarek, Jarosław, Jagodziński, Mieczysław
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.08.2022
Predmet:
Communication
decision support
dedicated genetic algorithm
Drones
Evacuations & rescues
last-mile delivery
Literature reviews
Logistics
Mathematical models
Mathematical programming
proactive and reactive approach
Traveling salesman problem
Trucks
unmanned aerial vehicle (UAV)
Unmanned aerial vehicles
vehicle routing problem with drones (VRPD)
Vehicles
ISSN:2076-3417, 2076-3417
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Shrnutí:Unmanned aerial vehicles (UAVs), also known as drones, are increasingly common and popular due to their relatively low prices and high mobility. The number of areas for their practical applications is rapidly growing. The most promising are: last-mile delivery, emergency response, the inspection of technical devices and installations, etc. In these applications, it is often necessary to solve vehicle routing problems, formulated as a variant of the vehicle routing problems with drones (VRPD). This study presents a proactive approach to a modified and extended VRPD, including: the dynamic selection of drone take-off points, bidirectional delivery (delivery and pick up), various types of shipments, allocation of shipments to drones and drones to vehicles, the selection of the optimal number of drones, etc. Moreover, a formal model of constraints and questions for the extended vehicle routing problem with drones (EVRPD) and exact and approximate methods for solving it have been proposed. The proposed model can be the basis for supporting proactive and reactive decisions regarding last-mile delivery, particularly the selection of the necessary fleet, starting points, the identification of specific shipments that prevent delivery with available resources, etc. The study also includes the results of numerous computational experiments verifying the effectiveness of the implementation methods. The time to obtain a solution is at least 20 times shorter for the proposed DGA (dedicated genetic algorithm) than for the mathematical programming solvers such as Gurobi or LINGO. Moreover, for larger-sized data instances, these solvers do not allow obtaining any solution in an acceptable time, or they obtain worse solutions.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app12168255