Adsanver, BirceGöktürk, Elvin ÇobanKoyuncu, Burcu Balçık2023-05-252023-05-252021http://hdl.handle.net/10679/8340https://doi.org/10.1007/978-3-030-64973-9_1We consider drones to support post-disaster damage assessment operations when the disaster-affected area is divided into grids and grids are clustered based on their attributes. Specifically, given a set of drones and a limited time for assessments, we address the problem of determining the grids to scan by each drone and the sequence of visits to the selected grids. We aim to maximize the total priority score collected from the assessed grids while ensuring that the pre-specified coverage ratio targets for the clusters are met. We adapt formulations from the literature developed for electric vehicle routing problems with recharging stations and propose two alternative mixed-integer linear programming models for our problem. We use an optimization solver to evaluate the computational difficulty of solving different formulations and show that both formulations perform similarly. We also develop a practical constructive heuristic to solve the proposed drone routing problem, which can find high-quality solutions rapidly. We evaluate the performance of the heuristic with respect to both mathematical models in a variety of instances with the different numbers of drones and grids.engrestrictedAccessbookPart12910.1007/978-3-030-64973-9_1Constructive heuristicDamage assessmentDronePost-disasterRouting2-s2.0-85102509142