Author: Zhang, Y.; Huang, S. X.; Gao, K. Y.; Zhang, L.; Ieee,; Huang, S.; Gao, K.
Title: Research on Lean Management Optimization of Intelligent Storage for Emergency Materials Based on Big Data Cord-id: kie8hl6f Document date: 2020_1_1
ID: kie8hl6f
Snippet: The Covid-19 once again warns us to take precautions before they happen. With the outbreak of the epidemic, all kinds of medical supplies and emergency rescue supplies have been in short supply or even fuse. Based on the background of big data analysis. Through research, it is found that due to the outbreak of the epidemic, the classic material allocation model cannot be applied to actual situations, and there is no way to achieve actual results. Therefore, based on the classic material allocati
Document: The Covid-19 once again warns us to take precautions before they happen. With the outbreak of the epidemic, all kinds of medical supplies and emergency rescue supplies have been in short supply or even fuse. Based on the background of big data analysis. Through research, it is found that due to the outbreak of the epidemic, the classic material allocation model cannot be applied to actual situations, and there is no way to achieve actual results. Therefore, based on the classic material allocation model, this paper-established the demand growth model and added GIS route planning to form a new material allocation, route selection, and cost comparison model to respond to the decision-making of rescue materials allocation and route selection in public emergency (epidemic, flood, fire), establish a mathematical model of material combination optimization and a mathematical model of route optimization planning, and use computers to solve the optimization plan.
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