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Routing a fleet of unmanned aerial vehicles: a trajectory optimisation-based matheuristic

Routing a fleet of unmanned aerial vehicles: a trajectory optimisation-based matheuristic
Routing a fleet of unmanned aerial vehicles: a trajectory optimisation-based matheuristic
This paper deals with a GRTOP that arises in the context of disaster assessment. We consider the problem where, in the aftermath of a disaster, a fleet of aerial gliders is required to photograph a number of waypoints (points of interest such as hospitals, schools and residential areas) and land in one of the available landing sites while optimising some performance criteria subject to operational constraints and flight dynamics. In our case, we aim at balancing the duration of the routes by minimising the maximum route flight time. To efficiently solve this GRTOP, we propose a hybrid method that is composed of two main building blocks: (i) a STO heuristic, designed to cope with the very challenging task of finding feasible (flyable) trajectories for a given route; and (ii) a routing matheuristic, capable of generating routes that can be evaluated by the STO procedure, that combines iterated local search and a set-partitioning-based integer programming formulation. The proposed algorithm was tested in randomly generated instances with up to 50 waypoints and it was capable of quickly finding feasible solutions.
Pereira Coutinho, Walton
844cd0ea-6cef-45fd-98f6-906493797077
Fliege, Joerg
54978787-a271-4f70-8494-3c701c893d98
Battarra, Maria
6ba9ac66-7d49-4849-b745-b4477b583acd
Subramanian, Anand
12026cc6-35f0-4a66-8806-e992fbd26d1e
Pereira Coutinho, Walton
844cd0ea-6cef-45fd-98f6-906493797077
Fliege, Joerg
54978787-a271-4f70-8494-3c701c893d98
Battarra, Maria
6ba9ac66-7d49-4849-b745-b4477b583acd
Subramanian, Anand
12026cc6-35f0-4a66-8806-e992fbd26d1e

Pereira Coutinho, Walton, Fliege, Joerg, Battarra, Maria and Subramanian, Anand (2018) Routing a fleet of unmanned aerial vehicles: a trajectory optimisation-based matheuristic

Record type: Monograph (Working Paper)

Abstract

This paper deals with a GRTOP that arises in the context of disaster assessment. We consider the problem where, in the aftermath of a disaster, a fleet of aerial gliders is required to photograph a number of waypoints (points of interest such as hospitals, schools and residential areas) and land in one of the available landing sites while optimising some performance criteria subject to operational constraints and flight dynamics. In our case, we aim at balancing the duration of the routes by minimising the maximum route flight time. To efficiently solve this GRTOP, we propose a hybrid method that is composed of two main building blocks: (i) a STO heuristic, designed to cope with the very challenging task of finding feasible (flyable) trajectories for a given route; and (ii) a routing matheuristic, capable of generating routes that can be evaluated by the STO procedure, that combines iterated local search and a set-partitioning-based integer programming formulation. The proposed algorithm was tested in randomly generated instances with up to 50 waypoints and it was capable of quickly finding feasible solutions.

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More information

In preparation date: May 2018

Identifiers

Local EPrints ID: 420643
URI: https://eprints.soton.ac.uk/id/eprint/420643
PURE UUID: cf7d854b-6025-466e-9d6e-72af7bd24624
ORCID for Joerg Fliege: ORCID iD orcid.org/0000-0002-4459-5419

Catalogue record

Date deposited: 11 May 2018 16:30
Last modified: 14 Mar 2019 01:39

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Contributors

Author: Walton Pereira Coutinho
Author: Joerg Fliege ORCID iD
Author: Maria Battarra
Author: Anand Subramanian

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