An efficient inventory model-based GA for food deterioration products in the tourism industry

Background: The inventory control practice of deteriorating food products that are subject to an expiration date is a challenging process. Inappropriate inventory control practice leads to substantial waste of products and significant holding and purchasing costs. Purpose: This paper aims to develop an inventory control model-based Genetic Algorithm (GA) to minimize the Total Annual Inventory Cost (TAIC) function developed explicitly for the proposed model. Methodology: GA is used and tailored to provide the best reorder level of deteriorating food products. A case study of one of the five-star hotels in Iraq is conducted, followed by a sensitivity analysis study to validate the proposed model for varying reorder levels. Results and Conclusion: A minimum inventory cost is obtained with an optimum reorder level achieved by running GA. It is concluded that the optimal reorder level provided by the proposed GA minimized the monthly inventory cost of products.