Economic order quantity model for growing items with seasonal dependent demand and deterioration

Abstract

The agricultural sector is characterised by seasonal fluctuations in the demand for its products. To address these demand variations, innovative Economic Order Quantity (EOQ) models are required to effectively manage inventory for growing items. Growing items refer to living organisms bred for human consumption, such as livestock, fish, and poultry. This paper presents a novel lot-sizing model for growing inventory items, specifically tailored to chickens. The proposed model considers a sinusoidal time-varying demand pattern with the exclusion of stochastic factors. In addition, it accounts for the constant deterioration of the slaughtered inventory that occurs during the consumption phase. The proposed EOQ model is developed over a finite time horizon and assumes no lead time when purchasing broiler chicks and no mortality of the chickens during their growth phase. The primary objective of this model is to minimise total costs whilst optimising the number of production cycles. To achieve this, we employ a derived mathematical model in conjunction with a computational algorithm. To provide practical insights into the model’s effectiveness, a numerical analysis was conducted to evaluate the performance of key system indicators such as the total cost, the number of production cycles and the number of chicks to be purchased under various scenarios. The key numerical findings showed cost reductions and an optimal number of production cycles ranging from eight to nine cycles. Furthermore, the convexity of the objective function was examined to ensure its stability and reliability. A comprehensive sensitivity analysis was also performed, offering valuable managerial guidance regarding the model’s applicability and robustness in real-world applications. Notably, the key findings from the sensitivity analysis indicate that deterioration and the duration of the production period have the most significant impact on total system costs. This research contributes to the existing inventory management literature by extending new considerations to EOQ models for growing items. Understanding inventory management in the agricultural sector, particularly for products that experience seasonal demand and susceptibility to deterioration, is essential for optimising agricultural productivity. The EOQ model developed in this research enables farmers to reduce spoilage by up to 9.4% and thus increase the potential profits obtained from their farming operations. Such considerations within the farming sector have become increasingly critical in addressing the challenges associated with achieving consistent harvests and yields. Effective inventory management practices in the agricultural sector can mitigate losses, streamline supply chain processes, and enhance overall efficiency. These practices ultimately support the sustainability of agricultural operations within dynamic market environments.