Comparative analysis of machine learning algorithms for demand forecasting under uncertainty

Doing business in present time is quite a challenging task. With the advent of technology, world is going through a complete transition. We are seeing 4th Industrial Revolution and Industry 5.0 is ready to hit the landscape. In this scenario managing Supply Chain (SC) for optimum performance is becoming a tedious task. Demand forecasting is playing a crucial role over the years for efficient and effective management and planning for competitive advantage. This paper aims to study the performance of various Machine Learning (ML) namely Linear Regression, Decision Tree Regression, Random Forest Regression, Support Vector Machine Regression, XG Boost Regression algorithms for demand forecasting under uncertainty. Keywords: Forecasting, Machine Learning, Supply Chain, Retail.