Maximising reward from a team of surveillance drones: A simheuristic approach to the stochastic team orienteering problem
Maximising reward from a team of surveillance drones: A simheuristic approach to the stochastic team orienteering problem
We consider the problem of routing a team of unmanned aerial vehicles (drones) being used to take surveillance observations of target locations, where the value of information at each location is different and not all locations need be visited. As a result, this problem can be described as a stochastic team orienteering problem (STOP), in which travel times are modelled as random variables following generic probability distributions. The orienteering problem is a vehicle-routing problem in which each of a set of customers can be visited either just once or not at all within a limited time period. In order to solve this STOP, a simheuristic algorithm based on an original and fast heuristic is developed. This heuristic is then extended into a variable neighbourhood search (VNS) metaheuristic. Finally, simulation is incorporated into the VNS framework to transform it into a simheuristic algorithm, which is then employed to solve the STOP.
Simheuristics, Simulation-optimisation, TOP, Team orienteering problem, UAVs, Unmanned aerial vehicles
485-516
Panadero, Javier
70cf8175-0e95-4239-9800-2732f8cfbb62
Juan, Angel
681f726e-e136-4028-816e-927f41c326d3
Bayliss, Christopher
6f5186e5-7c3b-4716-abca-6634b91c1440
Currie, Christine
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
2020
Panadero, Javier
70cf8175-0e95-4239-9800-2732f8cfbb62
Juan, Angel
681f726e-e136-4028-816e-927f41c326d3
Bayliss, Christopher
6f5186e5-7c3b-4716-abca-6634b91c1440
Currie, Christine
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Panadero, Javier, Juan, Angel, Bayliss, Christopher and Currie, Christine
(2020)
Maximising reward from a team of surveillance drones: A simheuristic approach to the stochastic team orienteering problem.
European Journal of Industrial Engineering, 14 (4), .
(doi:10.1504/EJIE.2020.108581).
Abstract
We consider the problem of routing a team of unmanned aerial vehicles (drones) being used to take surveillance observations of target locations, where the value of information at each location is different and not all locations need be visited. As a result, this problem can be described as a stochastic team orienteering problem (STOP), in which travel times are modelled as random variables following generic probability distributions. The orienteering problem is a vehicle-routing problem in which each of a set of customers can be visited either just once or not at all within a limited time period. In order to solve this STOP, a simheuristic algorithm based on an original and fast heuristic is developed. This heuristic is then extended into a variable neighbourhood search (VNS) metaheuristic. Finally, simulation is incorporated into the VNS framework to transform it into a simheuristic algorithm, which is then employed to solve the STOP.
Text
Currie__A_VNS_SimHeu_for_TOPST__EJIE__blind_
- Accepted Manuscript
More information
Accepted/In Press date: 13 October 2019
e-pub ahead of print date: 16 July 2020
Published date: 2020
Additional Information:
Funding Information:
The project is funded in part by the Spanish Ministry of Science, Innovation, and Universities (RED2018-102642-T) and the Erasmus+ Program (2019-I-ES01-KA103-062602).
Publisher Copyright:
Copyright © 2020 Inderscience Enterprises Ltd.
Keywords:
Simheuristics, Simulation-optimisation, TOP, Team orienteering problem, UAVs, Unmanned aerial vehicles
Identifiers
Local EPrints ID: 444063
URI: http://eprints.soton.ac.uk/id/eprint/444063
ISSN: 1751-5254
PURE UUID: 732d43dc-f842-4cd1-ab10-e104dd9ae123
Catalogue record
Date deposited: 23 Sep 2020 16:50
Last modified: 17 Mar 2024 05:55
Export record
Altmetrics
Contributors
Author:
Javier Panadero
Author:
Angel Juan
Author:
Christopher Bayliss
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
