A Fuzzy Inventory Model Using Pentagonal Fuzzy Numbers

Abstract

Transportation expenses may have an effect on significant business sectors. They could affect a company's price of goods as well as its capacity to remain competitive in the market. Another way to maximize transportation expenses is through inventory management. Prevent needless overstocking and incomplete shipments by keeping an accurate inventory and managing stock levels. This lowers the price of shipping extra items or broken shipments. Nonlinear Programming Kuhn Tucker Method is used to find the optimal solution, which has an impact on the monthly payment. The signed distance approach is used for defuzzification in the proposed model, and the Pentagonal fuzzy number is used to find the lowest cost. To test the inventory model, we create a CSV file and use Weka software to analyse the Economic Order Quantity and total cost.