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Master's Dissertation
DOI
https://doi.org/10.11606/D.55.2019.tde-29082019-091040
Document
Author
Full name
Joao Guilherme Cavalcanti Costa
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2019
Supervisor
Committee
Santos, Maristela Oliveira dos (President)
Gonçalves, José Fernando
Subramanian, Anand
Toledo, Cláudio Fabiano Motta
Title in English
The Vehicle Routing Problem with Drones
Keywords in English
Drones
Hybrid genetic algorithm
Logistics
Mixed Iiteger linear programming
Vehicle routing problem
Abstract in English
In this Dissertation, the Vehicle Routing Problem with Drones (VRPD), motivated by the growing interest on Unmanned Aerial Vehicles (UAVs, or Drones) by the industry and their applications in logistics is studied. A pioneer work by (MURRAY; CHU, 2015) shows a combination between UAV and a truck to deliver products, presenting an adaptation to the Traveling Salesman Problem (TSP). After a literature review, an extension of the model from Murray and Chu (2015) we present a model for the problem with multiple vehicles. This model is developed as a Mixed Integer Linear Programming (MILP) problem and solved with the solver CPLEX. A heuristic based on a Hybrid Genetic Algorithm (HGA) is also developed and presented. Our results show that the use of drones reduces the total mileage of the trucks by a significant percentage.
Title in Portuguese
O Problema do Roteamento de Veículos com Drones
Keywords in Portuguese
Algoritmo genético híbrido
Logística
Problema do roteamento de veículos
Programação linear Inteira mista
VANTs
Abstract in Portuguese
Nessa monografia estuda-se o Problema do Roteamento de Veículos com Drones (PRVD), motivado pelo crescente interesse da indústria em Veículos Aéreos Não Tripulados (VANTs) e suas aplicações em logística. O trabalho pioneiro de (MURRAY; CHU, 2015) mostra uma combinação entre VANT e um caminhão para realização de entregas de produtos, no qual foi proposta uma adaptação do Problema do Caixeiro Viajante (PCV). Após uma revisão de literatura, apresenta-se uma extensão do modelo de Murray and Chu (2015) para o problema com múltiplos veículos. Desenvolveu-se um modelo de Programação Linear Inteira Mista que foi resolvido com o solver CPLEX. Uma heurística basead em um Algoritmo Genético Híbrido também foi desenvolvido e é apresentada. Resultados mostram que a utilização dos VANTs reduzem a quilometragem dos caminhões significativamente.
 
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Publishing Date
2019-08-29
 
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