@inbook{0b80f0bbb4104b41af00f502c8d6eee4,
title = "A Genetic Algorithm Simheuristic for the Open UAV Task Assignment and Routing Problem with Stochastic Traveling and Servicing Times",
abstract = "Due to their flexibility, unmanned aerial vehicles (UAVs) are gaining importance in transportation and surveillance activities. The usage of UAV swarms raises the need for coordination and optimization of task assignments. Some of these operations can be modeled as team orienteering problems (TOP). This paper analyzes an open TOP in which a given fleet of homogeneous UAVs, initially located at a single depot, need to be coordinated in order to maximize the collection of rewards from visiting nodes without exceeding a maximum operation time. As in most real-life applications, both traveling times and servicing times at each node are modeled as random variables. To solve this NP-hard and stochastic optimization problem, a simheuristic based on the combination of a genetic algorithm with Monte Carlo simulation is proposed.",
author = "Juan, {Angel A.} and Alfons Freixes and Pedro Copado and Javier Panadero and Gomez, {Juan F.} and Carles Serrat",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.",
year = "2021",
doi = "10.1109/WSC52266.2021.9715292",
language = "English",
isbn = "978-1-6654-3312-9",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 Winter Simulation Conference, WSC 2021",
address = "United States",
}