Product-portfolio Ordering Analysis with Update Information in the Two-echelon: Risk Decision-making Model

This article proposes a two-echelon optimal ordering model for multi-product with Conditional Value-at-Risk (CVaR), which is popularly used in the field of financial engineering. Bayesian forecasting model under Brownian motion is adopted as the method of updating information, because it is more adaptable for the single-period product with strong stochastic characteristics. The model is then tested by simulative data, the outcome of which follows the real decision-making behavior completely. Moreover, the model can be formulated as a liner programming problem, which can be easily solved by the technique software.