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A learnheuristic approach for the team orienteering problem with aerial drone motion constraints

A learnheuristic approach for the team orienteering problem with aerial drone motion constraints
A learnheuristic approach for the team orienteering problem with aerial drone motion constraints
This work proposes a learnheuristic approach (combination of heuristics with machine learning) to solve an aerial-drone team orienteering problem. The goal is to maximise the total reward collected from information gathering or surveillance observations of a set of known targets within a fixed amount of time. The aerial drone team orienteering problem has the complicating feature that the travel times between targets depend on a drone’s flight path between previous targets. This path dependence is caused by the aerial surveillance drones flying under the influence of air-resistance, gravity, and the laws of motion. Sharp turns slow drones down and the angle of ascent and air resistance
influence the acceleration a drone is capable of. The route dependence of inter-target travel times motivates the consideration of a learnheuristic approach, in which the prediction of travel times is outsourced to a machine learning algorithm. This work proposes an instance-based learning algorithm with interpolated predictions as the learning module. We show that a learnheuristic
approach can lead to higher quality solutions in a shorter amount of time than those generated from an equivalent metaheuristic algorithm, an effect attributed to the search-diversity enhancing consequence of the online learning process.
machine learning, metaheuristics, team orienteering problem
1568-4946
Bayliss, Christopher
4c4de07f-5187-4bda-bb87-5d28d9f1f41b
Juan, Angel
f8b5781e-704e-4699-9841-97ddab494d8d
Currie, Christine
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Panadero, Javier
4d162d63-4f2e-4d8a-9ccd-1ecc71e30977
Bayliss, Christopher
4c4de07f-5187-4bda-bb87-5d28d9f1f41b
Juan, Angel
f8b5781e-704e-4699-9841-97ddab494d8d
Currie, Christine
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Panadero, Javier
4d162d63-4f2e-4d8a-9ccd-1ecc71e30977

Bayliss, Christopher, Juan, Angel, Currie, Christine and Panadero, Javier (2020) A learnheuristic approach for the team orienteering problem with aerial drone motion constraints. Applied Soft Computing, 92, [106280]. (doi:10.1016/j.asoc.2020.106280).

Record type: Article

Abstract

This work proposes a learnheuristic approach (combination of heuristics with machine learning) to solve an aerial-drone team orienteering problem. The goal is to maximise the total reward collected from information gathering or surveillance observations of a set of known targets within a fixed amount of time. The aerial drone team orienteering problem has the complicating feature that the travel times between targets depend on a drone’s flight path between previous targets. This path dependence is caused by the aerial surveillance drones flying under the influence of air-resistance, gravity, and the laws of motion. Sharp turns slow drones down and the angle of ascent and air resistance
influence the acceleration a drone is capable of. The route dependence of inter-target travel times motivates the consideration of a learnheuristic approach, in which the prediction of travel times is outsourced to a machine learning algorithm. This work proposes an instance-based learning algorithm with interpolated predictions as the learning module. We show that a learnheuristic
approach can lead to higher quality solutions in a shorter amount of time than those generated from an equivalent metaheuristic algorithm, an effect attributed to the search-diversity enhancing consequence of the online learning process.

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Final_A_Learnheuristic_Approach_to_the_Team_Orienteering_Problem_with_Aerial_Drone_Motion_Constraints - Accepted Manuscript
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More information

Accepted/In Press date: 1 April 2020
e-pub ahead of print date: 15 April 2020
Published date: July 2020
Keywords: machine learning, metaheuristics, team orienteering problem

Identifiers

Local EPrints ID: 440753
URI: http://eprints.soton.ac.uk/id/eprint/440753
ISSN: 1568-4946
PURE UUID: 9c332f6b-f79a-40ff-af71-c3bbf42f6e59
ORCID for Christine Currie: ORCID iD orcid.org/0000-0002-7016-3652

Catalogue record

Date deposited: 15 May 2020 16:31
Last modified: 28 Apr 2022 04:33

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Contributors

Author: Christopher Bayliss
Author: Angel Juan
Author: Javier Panadero

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