Abstract: The issue of post disaster material assistance, as the most important part of disaster relief, deserves widespread attention. At the same time, the methods of post disaster rescue also greatly affect the satisfaction of disaster victims. The satisfaction of the disaster victims directly reflects the problems that exist during the rescue process, and can also provide a certain reference for the next rescue activity. The most common problems in the process of material rescue are delayed arrival, shortage, and unfair distribution of materials. Therefore, these three indicators are determined as the important criteria for measuring the satisfaction of disaster victims.
   Considering the varying degrees of disaster suffered by disaster victims in different regions, the demand for these three indicators also varies. Therefore, the disaster victims in the disaster area are divided into three parts: heavy disaster area, medium disaster area, and light disaster area. In order to have a more accurate understanding of the needs of different disaster areas, a questionnaire survey is used to obtain different satisfaction standards for rescue efficiency and fairness for different types of people. At the same time, considering that different types of disaster victims may have different levels of satisfaction with different types of materials, multi material rescue is adopted. Three different types of materials are considered, namely food, medicine, and daily necessities. And we determine the priority of treating different types of materials based on on-site research,and quantify it as a satisfaction value and combine it with the previously determined satisfaction function to further improve a more practical satisfaction model.
   The established model aims to maximize the satisfaction of disaster victims, with limited supplies and vehicle loads as constraints. We simultaneously consider the corresponding genetic algorithm as the solution algorithm for the model,and slightly improve the algorithm by introducing a virtual distribution center, transforming the multi vehicle distribution problem into a single center vehicle routing problem. Taking Typhoon “Lichma” in 2019 as a case scenario, a case analysis is conducted to compare and analyze the rescue plans and corresponding satisfaction levels of each disaster site, with and without distinguishing satisfaction measurement standards.
   Through comparison, it can be concluded that under the condition of distinguishing satisfaction measurement standards, higher overall satisfaction can be achieved on the basis of the original satisfaction. The total delivery time is shorter, the total demand unmet rate is reduced, the total difference rate is reduced, and fair satisfaction is improved. The overall delivery plan is more efficient and targeted. It has been proven that dividing disaster areas into different satisfaction measurement standards and prioritizing materials is effective. Based on the traditional single standard satisfaction measurement standard, the model is more realistic, resulting in a more reasonable allocation of limited resources, prioritizing aid to severely affected areas, and fully utilizing corresponding different types of materials to avoid situations where material types and needs do not match. Future research can consider utilizing big data technology to timely collect, summarize, and update the needs of disaster victims, so as to improve the satisfaction model of disaster victims. At the same time, it is also possible to consider the psychological factors of disaster victims and quantify their psychology, which can better reflect the principles of humanitarian rescue.

Key words: disaster difference, satisfaction measurement standard, variety of materials, distribution of emergency supplies

摘要： 为有效解决因受灾差异导致灾民的满意度衡量标准不同,多种类物资优先级不同的问题,进而提高灾民对救援工作的满意度。通过实地调研得到各类型灾区对待救援效率及公平的不同满意度衡量标准,并确定各类型灾区对待不同种类物资的优先级。进一步完善出更符合实际的满意度模型。设计相应的遗传算法对模型进行求解,并将其应用于“利奇马”台风案例。结果表明,在考虑区分灾区满意度标准的情况下能够在原有满意度的基础上有所提高,在物资不充足运力有限的情况下,使整个物资分配过程更具针对性和有效性。

关键词: 受灾差异, 满意度衡量标准, 多种类物资, 应急物资分配