Accurate demand forecasting has become extremely important, particularly in the food
industry, because many products have a short shelf life, and improper inventory …

The traditional retailer had to deal with stocking of inventory and merchandising based on
raw estimates of his daily or weekly product sales to make available the right product at the …

Effective demand forecasting is vital for inventory management in retail. This study evaluates
five machine learning models—Linear Regression (LR), Decision Tree Regressor (DTR) …

Demand is defined as the propensity or willingness of customers to pay a certain amount of
price for a product or service they desire. Business entities use various forecasting …

The demand is often forecasted using econometric (regression) or statistical forecasting
methods. However, most of these methods lack the ability to model both temporal (linear and …

This paper proposes a novel forecasting method that combines the deep learning method–
long short-term memory (LSTM) networks and random forest (RF). The proposed method …

In this modern era of digitization, the competition is significantly increasing among retailers.
One of the major challenges for them is demand prediction or sales forecasting. Especially …

Time series forecasting plays a crucial role in various industries, particularly in predicting
product demand for effective supply chain management. This paper presents a novel …

Logistics demand forecasting plays a crucial role in regulating logistics management
activities, developing production plans, seeking maximum economic returns, and building …

Supply chain management (SCM) is a fast growing and largely studied field of research.
Forecasting of the required materials and parts is an important task in companies and can …