Sound waves with frequencies below the human hearing threshold in the range of 0.002 Hz to 20 Hz‎, ‎which are traveling through the atmosphere‎, ‎are referred to as infrasound‎. ‎Wind is the main noise in the above-mentioned frequency range‎. ‎The operation of receiving and detecting of infrasound are often hampered by wind‎. ‎Therefore‎, ‎high quality detectors are required‎. ‎For this purpose‎, ‎sensor arrays and array signal processing techniques are utilized‎. Fisher ratio-based signal detection is a widely used and powerful method in the field of infrasound‎. ‎The main drawback of this approach is its high computational time due to the repeated computation of test statistics for each element of the slowness grid‎. ‎Thus‎, ‎the researchers use a relatively low-resolution slowness grid in order to save time in processing‎. ‎On the other hand‎, ‎low resolution results in an error in the values of estimated parameters of infrasound waves‎. In this study‎, ‎a genetic algorithm based detection method is proposed in order to overcome the fundamental problems of the Fisher method‎. ‎In the proposed method‎, ‎the slowness grid components (p_x, p_y) are defined as the chromosome for the genetic algorithm‎. ‎Despite the previous methods‎, ‎the genetic algorithm has created the advantage that searching could be conducted in a continuous slowness grid‎. ‎Therefore‎, ‎the continuity of the network and searching only a limited number of slowness vectors reduce error rates and processing time respectively‎. ‎The apparent velocity and incoming angles became 0.5923 and 0.0710 respectively‎, ‎and the processing time decreased considerably from 25835.07 seconds to 533.55 seconds on average‎.