This research focuses on accurately forecasting steel wire mesh demand to ensure timely order fulfillment. Various univariate time series forecasting methods were employed, including Prophet, Support Vector Regression (SVR), 1-Dimensional Convolutional Neural Network (1D-CNN), Recurrent Neural...

This study examines the challenges of two warehouses operating under Last-In-First-Out (LIFO) order policies in inventory management, including unpredictable demand patterns, the decay of Weibull distribution, and the need to reduce carbon emissions by adopting green technology. The research...

Purpose: This paper investigates the impact of special replenishing modes within a 2-echelon inventory system under seasonal demand. Within this system, a periodic-review base-stock policy is employed. Two special replenishing modes are considered: emergency and transshipment in addition to a...

Purpose: This paper studies the problem that occurs on material purchase quantity in price uncertainty situation. Larger buying quantity when the price at high will increase the purchase amount while smaller buying quantity could risk the inventory level. The decision on the purchase quantity of...

Purpose: This study presents a systematic literature review that provides a broad and holistic view of how machine learning can be used and integrated to enhance decision-making in various areas of the supply chain, highlighting its combination with other techniques and models....