Multiple criteria risk averse model for multi-product newsvendor problem using conditional value at risk constraints

Abstract

Contemporary decision makers exhibit greater risk aversion than before and often have multiple performance criteria for comparing order quantities. Moreover, there is uncertainty in both demand and manager's risk preference. Uncertainties are also associated with suppliers, suppliers’ suppliers and transporters. Optimizing only profit does not consider risk in any way. To capture the risk associated with the decisions taken in multiproduct newsvendor scenario, there is a need to incorporate coherent risk measures in the classical newsvendor problems’ formulation. To address these issues, risk averse model for order quantity decision in a multi-product newsvendor scenario with multiple performance criteria using polyhedral-scalarized Conditional Value at Risk constraints is developed to establish quantified dominance of solution over the classical newsvendor solution. “Improvement Factor” is introduced to specify the degree of preference of the decision maker. We formulate the master problem and adopt a cut-generation algorithm to solve the problem and present a simulated numerical study to illustrate the application of the model. Building upon the results of the model, we draw significant inferences crucial to the development of a risk averse order policy framework. This is shown for newsvendor scenario but can be extended for multi stage inventory problems that future research can address.