Risk Analysis and Cost Management in Cold Chains

He Xiaoyan

Abstract

In the cold supply chain, products are subject to high risk of damages throughout the supply chain. It is therefore imperative that supply chain managers and logistic operators recognize these issues and take appropriate measures in ensuring that their shipments are managed adequately both from a cost and risk perspective. Hence, cold chain management is not simply one of minimizing cost, but rather one of finding the most cost-effective solution at some acceptable risk level. In this project, two main problems are studied for a local logistic company that deals with biologic products. The first problem is concerned with the packing optimization of their products. A mixed integer programming (MIP) model is proposed where the cost is minimized subject certain level of acceptable risk and other constraints. The MIP model is solved using Python and the Gurobi solver to find the optimal cost-risk solution. Sensitivity analysis is conducted for different demand scenarios and risk level. The second problem addressed help the company in the cold chain courier selection. An Analytic Hierarchy Process (AHP) model is developed to determine the best courier considering efficiency, cost and reliability as main criteria. The AHP model is implemented using YAAHP software and sensitivity analysis conducted. Overall, the models have been found to be helpful and effective to the company in managing their cold chain.