A Multi-Scenario Optimization Model for Emergency Cold Chain Logistics Distribution

Abstract

Cold chain logistics has been playing a more and more crucial role in modern society. As a special professional cold chain logistics, emergency cold chain logistics can provide quality assurance for temperature-sensitive products in emergency situations. Due to the fact that demand is uncertain in emergency situations, the cold chain logistics companies have to deal with the issue of uncertainty. However, there is no literature on the emergency cold chain logistics distribution optimization problem with uncertain demand. This research contributes to solving this problem. To deal with uncertain demand in emergency situations, an emergency cold chain logistics distribution optimization model with time windows is proposed based on scenario analysis. The objectives of the model are to minimize the total cost and shorten the delivery time simultaneously. The model can also optimize product procurement and refrigerated vehicle renting. The multi-scenario optimization model is applied to a Chinese cold chain logistics center to verify its effectiveness.