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

Chenxi Feng,Xin Liu,Yile Ba,Wenpeng Jia,Jianwei Ren,Rohit Salgotra

doi:10.1155/2021/1628162

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.

Highlights

Cold chain logistics is the technology and process that allows for the safe transport of temperature-sensitive goods and products along the supply chain [1, 2]
Demand is uncertain in emergency situations, which means that there are not enough historical data to estimate uncertain demand
According to the method of scenario analysis, the uncertain demand for two commodities, i.e., kiwi and dragon fruit, is divided into three important scenarios. e demand for the two commodities in each scenario is shown in Table 5. e demand is decreased in Scenario 1, as expected in Scenario 2, and increased in Scenario 3. e time windows of the eight wholesale markets are shown in Table 6. e number of available kiwi and dragon fruit is 10 tons and 8 tons, respectively

Summary

Introduction

Cold chain logistics is the technology and process that allows for the safe transport of temperature-sensitive goods and products along the supply chain [1, 2]. Cold chain logistics has been becoming a more and more crucial role in modern society [3]. E North America cold chain market was valued at 59.1 billion USD, which was the largest region in 2020. E Asia-Pacific region cold chain market was estimated to witness the fastest growth from 2021 to 2025 [5]. Emergency cold chain logistics plays an essential role in dealing with emergencies. The cold chain logistics industry plays a crucial role in the prevention and control of Coronavirus Disease 2019 (COVID-19). There is no literature on the emergency cold chain logistics distribution optimization model to deal with uncertain demand. Is paper will propose a multi-scenario optimization model to help managers distribute temperature-sensitive products under emergency situations more effectively There is no literature on the emergency cold chain logistics distribution optimization model to deal with uncertain demand. is paper will propose a multi-scenario optimization model to help managers distribute temperature-sensitive products under emergency situations more effectively

Methods

Results

Conclusion