Making informed inventory decisions, a revisit of the continuous review model, where back orders are allowed

Inventory management is the cornerstone of modern supply chain systems. It serves as an intermediate hub, facilitating the smooth transition of products between multiple supply nodes. In inventory models, the total cost is random, and it rarely matches the expected cost, leaving management unaware of actual cost fluctuations monitored and reported by accounting systems. The mean and variance approach has been employed to address this matter. However, most existing work either considers the decision maker’s attitude within the problem or treats it as a multi-objective problem, developing an efficient solution frontier. Unlike earlier studies, this research considers the mean and variance as a single-objective function, allowing the evaluation of the total cost at various risk levels (α). This approach enabled the determination of the probability distribution of the total cost, which led to a model that defines its boundary limits. Knowing these limits should help management make better-informed inventory decisions. The findings also show that the proposed and expected cost models follow the same optimal policy under certain conditions. These results are confirmed using a numerical example and validated by a simulation.