Abstract

The economic order quantity (EOQ) model is the most suitable and applicable inventory model for a supply chain consisting of a single retailer. Generally, an inventory model with a constant demand rate for a perishable item is inappropriate for customers’ changing habits. In the competitive world, market demand always changes with time and plays a crucial role in optimizing the supply chain. Initially, the demand rate was slow, but after some time, it gradually increased. Hence, in this paper, the price-dependent uniform demand rate is assumed to be used to develop the EOQ inventory model. Demand during the scheduling period occurs uniformly, and it varies with the selling price of the perishable item. The formulated model assumes two probabilistic deterioration rates (exponential and Weibull) at two separate time points in the inventory cycle. Next, the proposed EOQ inventory model is enriched with time-dependent linear holding costs under shortages, which are completely backlogged. The optimum order quantity is obtained by maximizing the profit expression of the inventory during the scheduling period, and the concavity of the model is checked and validated using a graphical technique. For the model, analytical solutions are difficult to obtain using the classical approach since the model is highly nonlinear. Hence, the genetic algorithm is a class of evolutionary algorithms that solves the formulated model. Lastly, sensitivity analysis of the model is discussed at different parameter values.

Author: Sandesh Kurade

Received on: April, 2023

Accepted on: May, 2024