The Distribution of Emergency Logistics Centers under the COVID-19 Lockdown: The Case of Yangtze River Delta Area

Abstract

The regular lockdown policy adopted in controlling the pandemic of COVID-19 has caused logistic disruptions in some areas that have a great impact on the living standards of residents and the production of enterprises. Given that the construction of emergency logistics centers is an effective solution, this paper takes the Yangtze River Delta Area (YRDA) of China as an example and discusses the site selection and material distribution of the emergency logistics centers in the region via a two-stage model. The first stage is the selection of candidate emergency logistics centers in the YRDA. A comprehensive evaluation index system is built with 4 primary and 15 secondary indexes to evaluate the logistic infrastructure capacity of the 41 cities in the YRDA. Further, through a principal component analysis, 12 cities are selected as candidate construction sites for emergency logistics centers. In the second stage, a biobjective site selection model with uncertain demand is established and calculated via the NSGA-II algorithm. According to the time sensitivity of emergency logistics, six cities are filtered from the optimal solution set, including Hefei, Hangzhou, Xuzhou, Wenzhou, Changzhou, and Shanghai, ensuring that all 41 cities are within their service scope.

Research on site selection of emergency material reserve based on set pair analysis and TOPSIS integration method: A case study of Hebei Province, China

“…n ) and satisfies Traffic factor [17] Highway density [17][18][19] Kilometre/ Square kilometer + Road freight volume [19,20] 100 millions tons + Natural environment and socio-demographic factors [21] Population [20] 10000 persons + Population density [18,[21][22][23][24] Person/ Square kilometer + Average annual precipitation [18,19,25] Millimeter -Average annual humidity [26] Percent -Economic factor [27] Maintenance cost [17,27,28] Yuan -GDP [18,20,25] 100 millions yuan + matrix Z = (z ij ) m×n under the action of weights.…”

Multi-Level Site Selection of Mobile Emergency Logistics Considering Safety Stocks

“…Constraint (6) shows that the emergency demand expectation obeys a normal distribution. Constraint (7) indicates that, at most, one facility is in the set of candidate sites for the distribution warehouse. Constraint ( 8) is used to constrain the maximum coverage of the distribution area of the distribution warehouse.…”

“…The risk coefficient of the rescue path is calculated based on the elastic time window, and decision support is provided for the path selection of emergency rescue. To solve the emergency demand uncertainty problem, Ge [7] introduced a two-stage model. The model is used to calculate the problem of the siting and material distribution of emergency logistics centers in the region.…”

Community Structure and Resilience of the City Logistics Networks in China

“…However, the logistics network communities may have potential effects on the structural vulnerabilities, and the failure of nodes in the network may affect the integrality and function of the community structure [13,14], thus having the detriment of certain industries and the entire economic system. During the lockdown in Shanghai in 2022, the automotive and auto-parts industries encountered an unprecedented crisis related to supply chain disruption.…”