Recently, the environment requires more emphasis on reverse logistics in order to maintain sustainability of the human civilization. The article introduces a sustainable model for reverse logistics that is based on two storage facility. Generally speaking, the essential commodities are...

Ever since the basic Economic Order Quantity (EOQ) model was introduced, several researchers and academicians extended and/or altered it, to reduce its unrealistic assumptions and make it more suitable and appropriate to the real world. The traditional EOQ Models assume constant demand and...

Background: Over the past decade, the potential advantages of employing deep learning models and leveraging auxiliary data in data-driven end-to-end (E2E) frameworks to enhance inventory decision-making have gained recognition. However, current approaches predominantly rely on feed-forward...

We explore using supervised learning with custom loss functions for multi-period inventory problems with feature-driven demand. This method directly considers feature information such as promotions and trends to make periodic order decisions, does not require distributional assumptions on...