Demand forecasting is an important task for retailers as it is required for various operational
decisions. One key challenge is to forecast demand on special days that are subject to vastly …

Forecasting future demand is of high importance for many companies as it affects
operational decisions. This is especially relevant for products with a short shelf life due to the …

Accurate and fast demand forecast is one of the hot topics in supply chain for enabling the
precise execution of the corresponding downstream processes (inbound and outbound …

Companies in the fashion industry are struggling with forecasting demand due to the short-
selling season, long lead times between the operations, huge product variety and ambiguity …

Retailers supply a wide range of stock keeping units (SKUs), which may differ for example in
terms of demand quantity, demand frequency, demand regularity, and demand variation …

Demand forecasting is of particular importance for retailers in the context of supply chains of
perishable goods and fresh food. Such goods are daily produced and delivered as they …

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 …

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

Seasonal demand forecasting is critical for effective supply chain management. However,
conventional forecasting methods face difficulties accurately estimating seasonal variations …

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 …