基于多元统计分析的火灾灾后抢险物资配送模型研究

传统物资配送方法存在配送物资效率低、配送成本高等缺点，为了及时确定抢险物资应急救援路线，向火灾受灾点快速配送抢险物资，提出基于多元统计分析的火灾灾后抢险物资配送模型。建模时采用多元统计分析法分析火灾受灾点救援需求和配送路线连通随机性，以及救援出发点对受灾点的最大覆盖范围的限制，利用加权贝叶斯算法将物资配送多目标规划问题转变成单目标规划问题，建立抢险物资配送单目标规划模型；运用遗传算法对模型求解，并采用惩罚函数处理模型中的约束条件，实现物资在受灾点之间均衡分配。

Research on Emergency Material Distribution Model after Fire Disaster Based on Multivariate Statistical Analysis

The traditional material distribution method has the disadvantages of low efficiency of distribution materials and high distribution cost. In order to determine the emergency rescue route of emergency materials in a timely manner, and quickly deliver emergency materials to the fire disaster point, a multi-statistical analysis model of fire disaster relief materials distribution based on multivariate statistical analysis is proposed. In the modeling, the multivariate statistical analysis method is used to analyze the rescue demand of the fire disaster site and the randomness of the distribution route, and the limitation of the rescue coverage point to the maximum coverage of the disaster point. The weighted Bayesian algorithm is used to transform the multi-objective planning problem of material distribution into a single The goal planning problem is to establish a target planning model for the rescue material distribution order;the genetic algorithm is used to solve the model, and the penalty function is used to deal with the constraints in the model to achieve balanced distribution of materials between the disaster points. The results show that the proposed method can improve the efficiency of distribution of rescue materials and reduce the distribution cost .