APPLICATION OF FUZZY LOGIC IN AGRICULTURAL NETWORK ANALYSIS FOR OPTIMIZING CROP PRODUCTION

This study investigates the application of fuzzy logic and fuzzy set theory in agricultural networking to identify the optimal paths for different crop production activities. Traditionally networking methods often face challenges with incomplete and uncertain data, which are prevalent in agriculture. Fuzzy logic using decagonal fuzzy number offers a more versatile method of handing imprecise data. In this study decagonal fuzzy numbers are defuzzified by rolling averages with a window of three to determine the optimal path. The solution of the formulated mathematical programming model is obtained using R software which enabling accurate computation of the best routes in agricultural networks and three different examples were taken and the network diagram is also shown. This paper further shows the scope of agriculture especially network path analysis in agriculture which can enhance decision making, which in turn can rise crop yields and improve agriculture productivity.