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Research on Lean Management Optimization of Intelligent Storage for Emergency Materials Based on Big Data

机译:基于大数据的应急材料智能存储精益管理优化研究

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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.
机译:Covid-19再次警告我们在发生之前采取预防措施。 随着疫情的爆发,各种医疗用品和紧急救援用品一直在供不应求甚至保险丝。 基于大数据分析的背景。 通过研究,发现由于流行病的爆发,经典的材料分配模型不能应用于实际情况,并且无法实现实际结果。 因此,基于经典的材料分配模型,本文建立了需求增长模型,并增加了GIS路线规划,形成了一种新的材料分配,路由选择和成本比较模型,以应对救援材料分配和路线的决策 在公共原体的选择(流行病,洪水,火灾),建立了物料组合优化的数学模型和路由优化规划的数学模型,并使用计算机解决优化计划。

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