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Inventory optimization focuses on stabilizing the stockpile management in the company with the expenditure involved in a successful volatile system. The major challenge is to meet the customer's demand in a well-organized way for profitable management. The nonlinear programming problem (NLP) from fixed order inventory systems, was solved by using the geometric programming method with fuzzification executed by decagonal fuzzy numbers and graded-mean representation as a defuzzification method. In this paper, we had minimized the total cost for an inventory model to obtain the optimal quantity and compared it with the fuzzy inventory model and illustrated with a numerically. [ABSTRACT FROM AUTHOR]

Businesses use inventory modelling to estimate the ideal level of inventories to be kept in a production process. This procedure entails controlling the quantity of goods or raw materials to be stoi-ed. the frequency of orders, and the supply flow. The primary task would be to reduce the overall cost incurred during the production process. This study examines a finite-life inventory model that permits a very small number of de fective products. illustrates the optimal order quantity. and explores how to optimal the second-degree total cost function while validating its optimality with a Hessian matrix. In addition. a numerical analysis is performed, and the findings are described. [ABSTRACT FROM AUTHOR]