基于不确定理论的应急物资配送问题研究

发布时间：2018-12-17 10:53

【摘要】：在突发事件的应急救援中,应急物资配送是最为重要的工作之一。应急物资及时送达物资需求点可以减少突发事件后由于救援工作延误而引发的进一步的生命和财产损失。针对突发事件的不确定性而导致的应急物资配送中的历史数据失效或者不存在需要由专家估计得出的情况,例如运输路况可能发生剧烈变化而导致原有的车辆运输时间等历史数据失效,例如因救援工作需要而成立的物资需求点对应急物资需求量的历史信息是不存在的等,本研究引入了不确定变量来描述应急物资配送中的专家估计参数,基于不确定理论,从不同资源约束的角度逐步深入构建基于不确定理论的应急物资配送模型,主要创新性成果如下:(1)针对应急物资配送过程中历史数据失效或不存在而需要专家估计的情况,引入不确定变量来描述应急物资配送中的数据参数,例如车辆运输时间和物资需求量等,创建了新的以车辆运输时间和最小为目标函数,车载重量限制为约束条件的应急配送规划模型。基于不确定理论,推导并证明了模型的清晰等价形式。设计了新的带元胞自动机的遗传算法(CGA)对模型进行求解,并通过数值例子例证了模型的应用,同时验证了 CGA算法求解的有效性和鲁棒性。(2)针对应急物资配送过程中车辆空间资源的约束,提出了三维装箱策略,创建了考虑三维装箱的应急物资配送的规划模型并基于不确定理论推导和证明了模型的清晰等价形式。由于应急物资的种类不同,为了方便装卸,应急物资在车厢中是需要分类摆放的。根据每种物资的包装箱长度不同的特点,提出了分类摆放的三维装箱策略,并根据装箱过程中箱子堆的高度、长度和宽度与车厢的高度、长度和宽度进行比较判断,避免出现车厢空间不满足需求物资摆放的车辆路径决策。新创建的模型为混合整数规划模型,本文改进了之前的CGA算法形成改进后的带元胞自动机的遗传算法(ICGA),并使用ICGA对模型进行求解。通过数值例子说明了考虑三维装箱的重要性,并验证了 ICGA算法的鲁棒性与有效性。(3)针对单出救中心的运力不足或者应急物资库存不足的情况,渐次研究并分别创建了不考虑空间资源约束和考虑空间资源约束的多出救中心应急物资配送规划模型。引入不确定变量,依据不确定理论,分别推导并证明了模型在不确定正态分布和不确定折线分布下的清晰等价形式。将多出救中心的车辆统一编码运输应急物资,解决单出救中心运力不足的问题。根据各应急物资的库存量,统一分配车辆的运输路线,解决单出救中心库存量不足的问题。最后使用ICGA算法对模型进行求解,并通过数值算例说明多出救中心的运输效率要高于单出救中心,并验证了算法的鲁棒性和有效性。
[Abstract]:In the emergency rescue, emergency material distribution is one of the most important work. The timely delivery of emergency materials to the material demand point can reduce the further loss of life and property caused by the delay of rescue work. In view of the uncertainty of an emergency event, the historical data in the distribution of emergency materials is invalid or there is no situation that needs to be estimated by experts, For example, the drastic changes in transport road conditions may lead to the failure of historical data such as the original vehicle transportation time. For example, the historical information of the material demand points set up as a result of the need for rescue work does not exist for emergency material requirements, and so on. In this study, uncertain variables are introduced to describe the expert estimation parameters in emergency material distribution. Based on uncertainty theory, the model of emergency material distribution based on uncertainty theory is constructed step by step from different resource constraints. The main innovative achievements are as follows: (1) for the situation where the historical data is invalid or does not exist in the process of emergency material distribution, the uncertain variables are introduced to describe the data parameters in the emergency material distribution. For example, vehicle transportation time and material demand, a new emergency distribution planning model with vehicle transportation time and minimum as objective function and vehicle weight restriction as constraint condition is established. Based on the uncertainty theory, the explicit equivalent form of the model is deduced and proved. A new genetic algorithm (CGA) of cellular automata is designed to solve the model, and the application of the model is illustrated by a numerical example. At the same time, the validity and robustness of CGA algorithm are verified. (2) aiming at the constraints of vehicle space resources in the process of emergency material distribution, a three-dimensional packing strategy is proposed. The planning model of emergency material distribution considering three dimensional packing is established, and the clear equivalent form of the model is deduced and proved based on the uncertainty theory. Because of the different types of emergency materials, emergency materials need to be classified in the carriage to facilitate loading and unloading. According to the characteristics of the different packing length of each kind of material, a three dimensional packing strategy is put forward, and the height, length and width of the container stack are compared with the height, length and width of the carriage during the packing process. Avoid the vehicle path decision in which the compartment space does not meet the demand. The new model is a mixed integer programming model. In this paper, the genetic algorithm (ICGA),) of the improved band cellular automata (BCA) is formed by improving the previous CGA algorithm and ICGA is used to solve the model. The importance of considering three-dimensional packing is illustrated by numerical examples, and the robustness and effectiveness of ICGA algorithm are verified. (3) in the case of insufficient transportation capacity of single rescue center or insufficient stock of emergency materials, The planning model of emergency material distribution of multi-out rescue center without space resource constraint and space resource constraint is studied and established gradually. By introducing uncertain variables and according to the theory of uncertainty, the clear equivalent forms of the model under uncertain normal distribution and uncertain broken line distribution are derived and proved respectively. In order to solve the problem of the shortage of transportation capacity, the vehicles of extra rescue center are coded to transport emergency materials. According to the stock of emergency materials, the transportation route of vehicles is distributed uniformly, and the shortage of stock in single exit rescue center is solved. Finally, the ICGA algorithm is used to solve the model, and a numerical example shows that the transport efficiency of the extra rescue center is higher than that of the single escape center, and the robustness and effectiveness of the algorithm are verified.
【学位授予单位】：北京科技大学
【学位级别】：博士
【学位授予年份】：2018
【分类号】：F224;F252

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