Machine Learning in Supply Chain (Logistic Analysis)
Machine Learning in Supply Chain (Logistic Analysis) Introduction Supply-chain management has been defined as the “design, planning, execution, control, and monitoring of supply chain activities to create net value, building a competitive infrastructure, leveraging logistics, synchronizing supply with demand, and measuring performance”. ML Applications in SCM ML applications that can be explored and implemented in the SCM space have been discussed in this section. 1. ML-based Demand Planning: Leading SCM vendors do offer functionality for Regression modeling or causal analysis for forecasting demand. The functionality is embedded in the DP module. However, if a more rigorous and advanced approach is desired, then one can forecast demand numbers outside of the SCM system using advanced modeling and then upload them back to the SCM system. Advanced modeling may include using advanced linear regression (derived variables, non-linear variables, ridge, lasso, etc.), de...