Route planning studies are of great importance for quadrotors, which are widely used in military and civil fields, to perform their duties autonomously and efficiently. In the study, a method is proposed that enables Quadrotor Route Planning (QRP) to be optimized with time priority and energy priority by using Genetic Algorithm (GA). For the proposed method, the Wind Effected QRP-App (WEQRP-App) desktop software was developed with the Visual Studio C# programming language. In the developed WEQRP-App, real location information from GMAP.Net map plugin and real wind data from the website of the General Directorate of Meteorology were used. Using Wind Effected Quadrotor Route Planning (WEQRP) method, more realistic planning was made before the flight and the flight efficiency was increased in terms of time and energy priority. Thus, it is foreseen that safer and less costly autonomous flights will take place when compared to the Standard QRP (SQRP) created without taking into account the wind effect, by avoiding the problems that arise due to unexpected energy consumption during the flight mission. When the results obtained from the proposed method were examined, it has been observed that WEQRP provides the improvements up to 13,5% in flight times and up to 27,4% in energy consumption according to SQRP.