A multi-objective approach to supply chain risk management: Integrating visibility with supply and demand risk

This paper investigates the relationship among supply chain visibility (SCV), supply chain risk (SCR), and supply chain cost of new and seasonal products. We assume that demand is probabilistic and comes from different scenarios such as forecasting, benchmarking, and market analysis data. For utilizing multi-attribute decision modeling, we build a model to maximize SCV and minimize both SCR and supply chain cost from an operational perspective. A heuristic algorithm based on a relaxation method on decision variables is proposed to solve an NP-hard model, and to show how a multi-objective approach provides near-optimum solutions. The results show that more visibility is desirable, because it increases efficiency in a supply chain and decreases both cost and risk.