摘要：Our economy and society depend on the continuousoperation of the internet and other wireless networks.However, during or after a natural disaster, communicationsinfrastructure can be affected and even interrupted. Effectiveplanning of emergency operations in these scenarios can playan essential role in saving lives. Recently, the use of UnmannedAerial Vehicles (UAVs) has been proposed to provide broadbandconnectivity. UAVs can be rapidly deployed as aerialbase-stations over the affected area and provide connectivitybetween victims and emergency operators. However, one ofthe challenges for their deployment in emergency scenarios isfinding their optimal locations to provide the largest number ofcommunication services. This paper introduces an optimizationmodel which positions UAVs in such a way as to maximize theircoverage (the number of mobile users covered), thus guaranteeinga successful voice service in an LTE network. A geneticalgorithm (GA) with a steady-state population configurationis used to find optimal locations of the UAVs. We presentthe results of the GA using two different representations:binary and floating-point. The results indicate that the geneticalgorithm with a steady-state model performs better using abinary representation.
