Rapidly restoring interconnected Information and Communication Technology (ICT) and power systems is crucial in major disasters. Advanced procedures involve communication between distributed power grid assets to form and synchronize self-contained grid islands at various voltage levels. However, disruptions in Information and Communication Technology (ICT) infrastructure can result in unrecoverable nodes, causing partial restoration and segmenting the power grid into isolated islands. This paper proposes an algorithm to optimally position Unmanned Aerial Vehicle Base Stations (UAV-BSs) to improve communication between these isolated grid islands. To use the minimum number of Unmanned Aerial Vehicles (UAVs) to reconstruct the network, it is necessary to employ a suitable algorithm to determine their positions. In this article, an algorithm is proposed to determine the position of UAVs using the minimum number of UAVs, while also considering other important goals in network reconstruction. Due to the multi-objective nature of the proposed algorithm, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) basic algorithm has been used. According to the conditions of the problem and to improve the proposed algorithm in terms of time and to avoid finding the local optimum, the initial population of the NSGA-II has been created using clustering algorithms. The evaluation is done on synthetic scenarios and real network models. The results show that a placement strategy can find a trade-off between the objectives of network recovery and communication quality, and the proposed initialization clustering improves the algorithm performance.