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Matheuristics for Multi-UAV Routing and Recharge Station Location for Complete Area Coverage

Rafael Santin, Luciana Pereira de Assis, Alessandro Vivas, Luciano C. A. Pimenta

2021Sensors28 citationsDOIOpen Access PDF

Abstract

This paper presents matheuristics for routing a heterogeneous group of capacitated unmanned air vehicles (UAVs) for complete coverage of ground areas, considering simultaneous minimization of the coverage time and locating the minimal number of refueling stations. Whereas coverage path planning (CPP) is widely studied in the literature, previous works did not combine heterogeneous vehicle performance and complete area coverage constraints to optimize UAV tours by considering both objectives. As this problem cannot be easily solved, we designed high-level path planning that combines the multiobjective variable neighborhood search (MOVNS) metaheuristic and the exact mathematical formulation to explore the set of nondominated solutions. Since the exact method can interact in different ways with MOVNS, we evaluated four different strategies using four metrics: execution time, coverage, cardinality, and hypervolume. The experimental results show that applying the exact method as an intraroute operator into the variable neighborhood descent (VND) can return solutions as good as those obtained by the closest to optimal strategy but with higher efficiency.

Topics & Concepts

Mathematical optimizationVariable neighborhood searchRouting (electronic design automation)Variable (mathematics)Computer scienceSet (abstract data type)MinificationPath (computing)Cardinality (data modeling)EnumerationMetaheuristicVehicle routing problemOperator (biology)MathematicsData miningComputer networkGeneBiochemistryChemistryMathematical analysisProgramming languageTranscription factorCombinatoricsRepressorRobotic Path Planning AlgorithmsUAV Applications and OptimizationVehicle Routing Optimization Methods
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