Regional directoreta election suggestion for ÇAYKUR Enterprises

In this study; the positions of regional directorates belonging to the General Directorate of Tea Enterprises (Çaykur), which is one of the leading brands of the Turkish tea sector and also a state economic enterprise, has been optimized. The use of artificial intelligence is also expanding due to the advancement of technology. In a globalised world and ever-increasing competitive environment, artificial intelligence and techniques for businesses become inevitable. Especially in matters where investment costs such as facility location selection are high, the decisions that businesses make are strategically important. In this context; optimizing the distance between Çaykur and authorized outlets will contribute to both Çaykur and the Turkish economy due to the state economic enterprises characteristics of Çaykur. In this study, k-means clustering analysis method, one of the machine learning techniques and nonlinear programming method one of the operations research techniques, were used to optimize the locations of regional directorates. In this study, K-Means Clustering Analiysis which are popular in solving clustering problems, with Nonlinear Programming Methods have been applied together in the problem of selecting a facility location. For this reason, this study fills a gap in the literature and therefore, this study is important academically and scientifically. According to the results obtained; when the analysis methods are modeled together as a hybrid, the results become more effective.