Institutional Repository
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Solving the drone routing problem for pick up and deliveries between customers using a grasp/vns hybrid algorithm

Aronis Stylianos

Full record


URI: http://purl.tuc.gr/dl/dias/8F044812-7A3C-426B-A10C-B87C67B08773
Year 2022
Type of Item Diploma Work
License
Details
Bibliographic Citation Stylianos Aronis, "Solving the drone routing problem for pick up and deliveries between customers using a grasp/vns hybrid algorithm", Diploma Work, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2022 https://doi.org/10.26233/heallink.tuc.92913
Appears in Collections

Summary

Globalization and the ongoing increase in the demand for more efficient methods to transport goods throughout the world have become the critical factor that led to the continuous improvement of the supply chain and the development of new technologies. To achieve this goal, either the existing methods are improved or new ones are created to increase the efficiency of the collective, managerial and distributional systems so that economies can co-exist with the constant increase of market demands. A new and very promising method of better distribution is through the air with the assistance of Drones. In this work, we examine and solve the routing problem of such vehicles for a supply chain with multiple sellers and buyers. We try to achieve an efficient way to connect each seller with their correspondent buyer. The goal is to determine the best route, starting from the base, that the Drones must follow in order to minimize the energy consumption of their batteries. The position of the base, that the drones start and end their route, is known. We also assume that the customer state (seller or buyer), position, their connections in the plane as well as the energy consumptions constraints for the drones are known when starting solving the problem. For the solution we use a hybrid algorithm which combines the Greedy randomized adaptive search procedure (GRASP) and the variable neighborhood search (VNS). All algorithms were created using the Visual Studio environment with the C++ language. All results are presented analytically.

Available Files

Services

Statistics