废旧家电逆向物流模式选择及网络构建研究

发布时间：2018-02-28 13:22

本文关键词： 废旧家电逆向物流模式选择收益最大化网络构建遗传算法　出处：《北京交通大学》2015年硕士论文　论文类型：学位论文

【摘要】：作为家电消费大国,我国已步入了家电报废高峰期,家电产品更新换代的同时,也带动着废旧家电逆向物流的发展。我国借鉴了国外实施的“生产责任延伸制”,制定了相关的政策制度,引导家电制造商参与到逆向物流中,然而这些政策并没得到有效落实,很多制造商没有进行合理规划就盲目实施逆向物流,导致大量废旧家电仍然流入非正规回收渠道和拆解市场,造成资源浪费和环境污染。制造商在开展逆向物流业务前,需要先选择合适的逆向物流模式,然后在模式选定地基础上构建合理的逆向物流网络。对此,本文基于制造商的立场,以制造商收益最大化为目标,研究废旧家电逆向物流模式和网络构建具有重要的现实意义。本文首先界定了废旧家电逆向物流定义,分析了废旧家电逆向物流的特点和运作流程；根据废旧家电回收和处理主体不同,将废旧家电逆向物流模式分为自营模式、联合模式以及外包模式,并分别定性分析了这三种模式的优缺点,比较了它们在影响因素方面表现的不同；基于废旧家电逆向物流网络结构类型划分,分析了三种模式下的网络结构特点；其次,提出了不同模式下的废九家电逆向物流收益最大化模型,利用Stackelberg博弈思想求出了各模型的最优解,分析了回收投资效率和处理努力系数两个参数的取值情况对制造商最大收益值的影响,继而影响到模式选择结果,并通过算例进行了验证；然后,侧重于自营模式,进行网络构建研究,明确了网络构成要素和网络结构类型,设计了五层多品类正／逆闭环型网络拓扑结构,建立了以收益最大化为目标的混合整数规划模型来进行合理选址和节点之间流量分配；最后,提出了该网络构建模型的求解思路,设计了选址和流量分配同时解决的遗传算法步骤,通过算例和算法中参数的灵敏度分析,运用Python2.7.3进行仿真计算,验证了模型和算法的有效性和合理性。
[Abstract]:As a large consumer of household appliances, our country has stepped into the peak period of household appliance scrapping, and at the same time, the household appliances products have been upgraded. It also leads to the development of reverse logistics for used and used household appliances. Our country draws lessons from the "extended system of production responsibility" implemented by foreign countries, formulates relevant policies and regulations, and guides home appliance manufacturers to participate in reverse logistics. However, these policies have not been effectively implemented. Many manufacturers blindly implement reverse logistics without reasonable planning, which leads to a large number of waste appliances still flowing into the informal recycling channels and dismantling markets, resulting in waste of resources and environmental pollution. It is necessary to select the appropriate reverse logistics model first and then construct a reasonable reverse logistics network on the basis of the mode selection. In this paper, based on the manufacturer's position, the goal is to maximize the profit of the manufacturer. It is of great practical significance to study the reverse logistics model and network construction of waste appliances. This paper first defines the definition of reverse logistics of waste household appliances, analyzes the characteristics and operation process of reverse logistics of waste appliances, and divides the reverse logistics mode of waste appliances into self-supporting mode according to the different recovery and treatment main body of waste appliances. Combined mode and outsourcing mode, and respectively qualitative analysis of the advantages and disadvantages of these three models, compared their different performance in the impact factors; based on the classification of waste electrical appliances reverse logistics network type, The characteristics of network structure in three modes are analyzed. Secondly, the model of maximizing the profit of waste nine household appliances reverse logistics under different modes is put forward, and the optimal solution of each model is obtained by using Stackelberg game theory. This paper analyzes the influence of the two parameters of the return investment efficiency and the processing effort coefficient on the maximum profit value of the manufacturer, and then influences the result of the mode selection, and verifies it through an example. Then, it focuses on the self-supporting mode. This paper studies the network construction, defines the network elements and network structure types, and designs a five-layer and multi-category forward / inverse closed loop network topology. A hybrid integer programming model with the goal of maximizing income is established to carry out reasonable location and flow allocation between nodes. Finally, the solution of the network model is proposed. The steps of genetic algorithm are designed to solve the problem of location selection and flow allocation simultaneously. The validity and rationality of the model and algorithm are verified by using Python2.7.3 and the sensitivity analysis of the parameters in the algorithm.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F426.6;F713.2;TP18

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