Abstract
In this paper, we introduce the Glider Routing and Trajectory Optimisation Problem (GRTOP), the problem of simultaneously finding optimal routes and trajectories for a fleet of gliders with the aim of surveying a set of locations. We propose a novel Mixed-Integer Nonlinear Programming (MINLP) formulation for the GRTOP, which optimises the routes as well as the trajectories along these routes, while flight dynamics is modelled as constraints. We avoid solving a non-convex problem by linearising the gliders’ flight dynamics, converting the proposed MINLP into a Mixed-Integer Second-order Cone Programming (MISOCP) problem. To allow for a more tractable formulation, the dynamical constraints are relaxed and a penalisation is added to the objective function. Several different discretisation techniques are compared. The formulation is tested on instances inspired by risk maps of flooding-prone cities across the UK and on 180 randomly generated instances.
Original language | English |
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Pages (from-to) | 1138-1154 |
Number of pages | 17 |
Journal | European Journal of Operational Research |
Volume | 274 |
Issue number | 3 |
Early online date | 8 Nov 2018 |
DOIs | |
Publication status | Published - 1 May 2019 |
Keywords
- OR in disaster relief
- Routing
- Trajectory optimisation
- Unmanned gliders
ASJC Scopus subject areas
- Computer Science(all)
- Modelling and Simulation
- Management Science and Operations Research
- Information Systems and Management
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Maria Battarra
- Management - Professor
- Information, Decisions & Operations - Director of Studies MSc in Management suite
- Made Smarter Innovation: Centre for People-Led Digitalisation
Person: Research & Teaching