供应中断下考虑风险态度的四级设施选址—库存模型与算法研究

发布时间：2018-04-04 10:27

本文选题：四级供应链　切入点：选址-库存模型　出处：《东北大学》2014年硕士论文

【摘要】：近年来,企业对供应商的选择及设施选址-库存问题越来越重视,这对解决设施选址-库存问题提出了新要求。而且,全球供应链中断事件对企业整体运行产生了严重的影响。因此,针对供应中断背景下,设施选址-库存问题的研究是具有现实意义的挑战性课题。目前,关于多级设施选址-库存问题的已有研究大多关注企业花费的经济效益,忽略企业面临的风险；关于供应链风险管理的研究大多关注供应链整体规划完成后,如何进行风险防御管理或者应急管理,未将可能发生的风险事件融入到模型构建中,也未考虑决策者风险态度对供应链最优决策的影响。本文在此基础上,构建了供应中断下考虑风险态度的四级设施选址-库存控制模型,主要工作包括：(1)考虑供应商选择的四级设施选址-库存模型构建。在传统的三级设施选址-库存模型中融入上游供应商的选择,对整个供应链中的收入以及各环节产生的成本进行详细建模计算,得到不考虑供应中断情况下的四级供应链选址-库存模型。(2)供应中断下考虑风险态度的四级设施选址-库存控制模型构建。将供应中断的随机性以概率的方式融入到四级设施选址-库存模型中,构建考虑供应中断实际发生情况的四级设施选址-库存控制模型。接着,利用均值-方差理论将风险态度系数融入到供应中断下的四级设施选址-库存模型中,考虑决策者风险态度不同对供应链设计的影响。(3)基于粒子群优化算法的算法设计与求解。对构建的模型进行算法设计,由Matlab软件编程,以中石油东北化工销售公司为案例,验证模型和算法的可行性和有效性。接着,通过对供应中断概率和风险态度系数进行灵敏度分析,求得各种不同情况下的结果,得到一系列有关供应中断下考虑风险态度的选址-库存模型决策的相关见解。本文构建的供应中断下的四级设施选址-库存模型是对单纯进行设施选址-库存决策模型的补充,使模型更贴近实际情况,一定程度上有助于提高供应链整体利润,并能抵御一定的风险。最终由粒子群算法对中石油东北化工销售公司算例进行求解,得到一系列结论,对企业实际运作所需提供了一定的指导意义。
[Abstract]:In recent years, enterprises pay more and more attention to supplier selection and facility site-inventory problem, which puts forward new requirements to solve facility site-inventory problem.In addition, the global supply chain disruption has a serious impact on the overall operation of the enterprise.Therefore, under the background of supply interruption, the research of facility location-inventory problem is a challenge with practical significance.At present, most of the existing researches on the site-inventory problem of multi-level facilities focus on the economic benefits of the enterprises' costs and ignore the risks faced by the enterprises, and most of the studies on the supply chain risk management focus on the supply chain after the completion of the overall planning.How to carry out risk defense management or emergency management does not incorporate the possible risk events into the model building, nor does it consider the impact of decision makers' risk attitude on the optimal decision of supply chain.On this basis, this paper constructs a four-level facility site-inventory control model considering risk attitude under supply interruption. The main work includes: 1) Construction of four-level facility site-inventory model considering supplier selection.The selection of upstream suppliers is incorporated into the traditional three-level facility site-inventory model, and the revenue in the whole supply chain and the cost generated by each link are modeled and calculated in detail.A four-level supply chain site-inventory model without considering the supply interruption is obtained. (2) the four-level facility site-inventory control model with risk attitude under supply interruption is constructed.The randomness of supply interruption is incorporated into the site-inventory model of four-level facility in a probabilistic way, and a four-level facility location-inventory control model considering the actual occurrence of supply interruption is constructed.Then, by means of mean-variance theory, the risk-attitude coefficient is incorporated into the four-level facility site-inventory model under supply interruption.Considering the influence of decision makers' different risk attitude on supply chain design, the algorithm design and solution based on particle swarm optimization (PSO).The algorithm of the model is designed and programmed by Matlab software. The feasibility and validity of the model and algorithm are verified by a case study of PetroChina Northeast Chemical Marketing Company.Then, through the sensitivity analysis of supply interruption probability and risk attitude coefficient, the results under different conditions are obtained, and a series of relevant opinions about site-inventory model decision considering risk attitude under supply interruption are obtained.The four-level facility site-inventory model constructed in this paper is a supplement to the facility site-inventory decision model, which makes the model more close to the actual situation, and to some extent helps to improve the overall profit of the supply chain.And can resist certain risk.Finally, the particle swarm optimization algorithm is used to solve the example of PetroChina Northeast Chemical Marketing Company, and a series of conclusions are obtained, which provide a certain guiding significance for the actual operation of the enterprise.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F274;F426.22;F224

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