Abstract
The effective distribution of public storage materials is the key to realizing rapid and accurate rescue of territories, which could truly solve the “last kilometer” problem of emergency rescue. At present, it is relatively rare to study the rapid and accurate distribution of emergency supplies by taking demand forecasts, emergency reserves, and distribution models as an organic whole. In view of the bottleneck of rapid and accurate rescue in the complex disaster environment, this paper selects various means such as field research, literature retrieval, and previous case analysis and uses the system analysis method. Next, this paper explains that the three main factors that affect the distribution of public storage materials are the demand of “black box”, the scarcity of materials, and the blindness of distribution and constructs an effective analysis framework of demand predictability, material availability, and distribution accuracy. Finally, this paper puts forward the triangle structure framework of demand forecasting, virtual public storage, and comprehensive distribution and further explains the triangle structure relationship, operation mechanism, and operation strategy of effective distribution of public storage materials.
Highlights
In recent years, the frequency of natural disasters in China has been significantly higher than usual, and the scale has been wider
Pang [7] first used a BackPropagation neural network to predict the demand for emergency materials and established an emergency material distribution model consisting of emergency material supply points, transit points, and disaster points
In order to eliminate the influence of three major factors in the shortest time, solve the problem of rapid and accurate material distribution in the territory, and ensure the efficiency of emergency rescue, this paper proposes an analysis framework of the effectiveness of the distribution of local public storage materials
Summary
The frequency of natural disasters in China has been significantly higher than usual, and the scale has been wider. The research shows that the death toll increases rapidly within 24 h after the disaster, reaching the maximum within 8 to 16 h [2] This means that emergency rescue must fill the vacuum of rescue as quickly as possible, quickly deliver materials to the disaster area [3], and save lives to the greatest extent possible. Xu [6] used a BackPropagation neural network to predict emergency material demand and established an emergency material allocation model. In the past practice of emergency area, China has made some achievements in rapid and accurate rescue but, at present, it is relatively rare to study the rapid and accurate distribution of emergency supplies by taking demand forecasts, emergency reserves, and distribution models as an organic whole. This paper analyzes the factors that affect the effectiveness of emergency delivery in territories, constructs an effective analysis frame and a triangular structure frame, and provides a theoretical basis for solving the “last kilometer” problem of rapid and accurate rescue
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