Precipitation is an important factor in meteorology having both spatial and temporal variation. Studying the spatial distribution of precipitation needs numerous points for monitoring so that they will be well-distributed in the particular region. Density determination and proper distribution of rain gauges in rain gauging networks of each region are paramount steps in the triumph of water projects and regional planning; furthermore, it improves the efficient use of information. In recent years, various investigations related to applying geostatistical methods have been conducted for optimizing the location of rain gauge stations. Entropy approach has also been applied in recent studies as an optimization method. In this study, Gavkhouni basin was investigated under two scenarios using monthly precipitation data of 38 rain gauge stations. The first scenario gives the amount of transinformation of intended stations using MATLAB software by Entropy estimation of each station. Transinformation is then divided into five categories after the obtained data is standardized. The stations in which the amount transinformation is categorized as weak and very weak are recognized and the locations for installing extra stations are determined based on the distribution of transinformation. Five stations were added to the existing ones in this scenario. In the second scenario, it was assumed that there is no station in the region and the optimum locations for all 38 stations were specified. This was done by improving correlation coefficient among the produced precipitation data by cuckoo optimization algorithm which was expanded in MATLAB environment and the amount of transinformation in all parts of the region was achieved. The location of optimal stations was determined based on the average of produced data. The results showed that the magnitude of transinformation increased. Key words : Transinformation Entropy, Geostatistics, Kriging, Optimization, Evolutionary algorithm, Cuckoo algorithm