不确定环境下逆向物流系统的构建与优化
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摘要
逆向物流是相对于传统正向物流而言的一种新型物流控制模式,主要研究如何有效实现产品的回收与再利用。逆向物流的实施可以带来巨大的经济效益、社会效益和环境效益。不确定性是逆向物流的最大特点,也增加了逆向物流系统构建与优化的难度。本文结合国家863课题,以废旧家电为研究对象,总结了逆向物流管理的研究现状,分析了逆向物流的不确定性,并预测了废旧产品的回收水平。在此基础上,深入研究了回收模式决策、回收网络架构、动态性能优化等方面的内容,并设计了系统的信息服务平台。本文的研究可为逆向物流系统的构建提供科学的理论基础和方法指导。
第一章回顾了论文研究的背景,阐明了论文研究的意义。描述了逆向物流的相关概念。论述了论文相关领域的国内外研究现状。最后给出了论文的研究思路和框架。
第二章在分析逆向物流系统不确定的基础上,描述了逆向物流的不确定性衍生机理概念模型,研究了基于模糊理论的系统构建与优化方法体系。接着基于产品全生命周期,分析了影响废旧产品回收数量和回收时间的主要因素,建立了回收水平的模糊神经网络预测模型。
第三章对比分析了常见的逆向物流回收模式的特征。重点针对制造商自营、经销商负责以及第三方部分负责这三种回收模式,对应建立了模糊不确定环境下的双层规划模型,在Stackelberg框架下进行了模型的求解,考虑到回收方的投资效率和制造商的风险偏好,定量比较分析了各回收模式的最优均衡零售价、回收率、批发价以及供应链各成员利润,并从供应链整体的优化角度判断了制造商决策的合理性。为了保证逆向物流外包模式时合作关系的稳定性,设计了合作契约下的回收利益分配机制。
第四章描述了逆向物流网络的组成与各设施的功能,根据与正向物流网络的关联程度,分析了三种典型的网络组织结构。以网络运作总成本最小为优化目标,建立了逆向物流网络的通用优化模型,模型中考虑了产品回收量、需求量以及各设施处理能力的不确定性,心用模糊机会约束规划方法将模型转化成了清晰化等价形式,并提出了一种自适应动态调整惯性权重的粒子群算法进行求解。进而探讨了网络结构的环境适应能力,构建了性能稳健指数来评价设计网络的稳健性。
第五章研究了环保策略、再制造能力扩张策略以及不同市场行为等外部因素对逆向物流系统中长期的影响,建立了SD模型对系统性能进行了动态仿真。通过选择不同的参数组合分析了不同情形下的系统性能,为政策制定者和决策者对逆向物流系统进行中长期的动态规划提供了一个有用的工具。
第六章在论文理论研究的基础上,对逆向物流信息服务平台进行了需求分析,描述了平台的总体结构和功能模型。
第七章对总结了本文研究所取得的成果,并指出了今后进一步的研究方向。
Compared with traditional forward logistics, reverse logistics aiming to reuse and recycle effectively is a new logistics control mode with huge economic, social and environmental benefits. Uncertainty is the most obvious characteristics which increases the difficulty of design and optimization for system. Sponsored by the Chinese National Programs for High Technology Research and Development, based on in-depth analysis of uncertainty and forecast of waste products recovery level, this dissertation focused on take-back mode, network construction, performance optimization and information platform of reverse logistics. It provided a solid theoretical basis and guidance method for construction of reverse logistics system.
In chapter one, background and significance of research paper were stated. Concept of reverse logistics was described. Research state at home and abroad of related fields were summarized. Then main research structure and method were presented.
In chapter two, uncertainty of the system was analyzed and uncertain derived mechanical model of reverse logistics was described. Construction and optimization methodology architecture was researched based on fuzzy theory. Then main factors affecting the number of recycling waste products and recycling time were analyzed based on product life cycle. A fuzzy neural network prediction model of recovery level was presented.
In chapter three, characteristic of common reverse logistics model was compared. Focusing on three types of take-back modes in market with leader of manufacturer, distributor or third-party, corresponding bilevel programming models for each mode under fuzzy environment were set up and then solved in Stackelberg game framework. Taking investment efficiency and risk preference into account, the optimal retail prices, product return rates, wholesale price and profits of channel members of each mode were compared quantatively. Rationality of manufacturer decision was judged from perspective of whole supply chain. In order to ensure relationship in outsourcing mode stable, assignment mechanism of recovery benefit under the contract was designed.
Chapter four described reverse logistics network structure and facilities function. According to liasion with forward logistics network, three kinds of typical network organization structure were analyzed. Taking minimum total operation cost as optimization objective, a common model of network structure was developed. Regarding quantity and demand of returned products and facilities capacity as fuzzy parameters, the proposed model was solved by converting fuzzy chance constraints to their respective crisp equivalents. A new adaptive particle swarm optimization algorithm with dynamically changing inertia weight was brought forward to solve the problem. Then environmental adaptability of network was discussed, and performance robustness index was designed to evaluate network robustness.
Chapter five examined the impact of environmental issues on long-term behaviour of reverse logistics system. The environmental issues examined were environmental protection strategy, remanufacturing capacity expansion strategy and market behavior. Behaviour of system was analyzed through a dynamic simulation model based on the principles of the system dynamics methodology. The dynamic model provided a useful tool, which can be used to evaluate the effect of environmental issues on long-term decision making in collection and remanufacturing activities.
In chapter six, based on forword theoretical studies, demand analysis of reverse logistics information platform was carried on. Structural and functional model of platform was built up.
In chapter seven, main conclusions of this dissertation were summarized and further research issues were put forward.
第一章回顾了论文研究的背景,阐明了论文研究的意义。描述了逆向物流的相关概念。论述了论文相关领域的国内外研究现状。最后给出了论文的研究思路和框架。
第二章在分析逆向物流系统不确定的基础上,描述了逆向物流的不确定性衍生机理概念模型,研究了基于模糊理论的系统构建与优化方法体系。接着基于产品全生命周期,分析了影响废旧产品回收数量和回收时间的主要因素,建立了回收水平的模糊神经网络预测模型。
第三章对比分析了常见的逆向物流回收模式的特征。重点针对制造商自营、经销商负责以及第三方部分负责这三种回收模式,对应建立了模糊不确定环境下的双层规划模型,在Stackelberg框架下进行了模型的求解,考虑到回收方的投资效率和制造商的风险偏好,定量比较分析了各回收模式的最优均衡零售价、回收率、批发价以及供应链各成员利润,并从供应链整体的优化角度判断了制造商决策的合理性。为了保证逆向物流外包模式时合作关系的稳定性,设计了合作契约下的回收利益分配机制。
第四章描述了逆向物流网络的组成与各设施的功能,根据与正向物流网络的关联程度,分析了三种典型的网络组织结构。以网络运作总成本最小为优化目标,建立了逆向物流网络的通用优化模型,模型中考虑了产品回收量、需求量以及各设施处理能力的不确定性,心用模糊机会约束规划方法将模型转化成了清晰化等价形式,并提出了一种自适应动态调整惯性权重的粒子群算法进行求解。进而探讨了网络结构的环境适应能力,构建了性能稳健指数来评价设计网络的稳健性。
第五章研究了环保策略、再制造能力扩张策略以及不同市场行为等外部因素对逆向物流系统中长期的影响,建立了SD模型对系统性能进行了动态仿真。通过选择不同的参数组合分析了不同情形下的系统性能,为政策制定者和决策者对逆向物流系统进行中长期的动态规划提供了一个有用的工具。
第六章在论文理论研究的基础上,对逆向物流信息服务平台进行了需求分析,描述了平台的总体结构和功能模型。
第七章对总结了本文研究所取得的成果,并指出了今后进一步的研究方向。
Compared with traditional forward logistics, reverse logistics aiming to reuse and recycle effectively is a new logistics control mode with huge economic, social and environmental benefits. Uncertainty is the most obvious characteristics which increases the difficulty of design and optimization for system. Sponsored by the Chinese National Programs for High Technology Research and Development, based on in-depth analysis of uncertainty and forecast of waste products recovery level, this dissertation focused on take-back mode, network construction, performance optimization and information platform of reverse logistics. It provided a solid theoretical basis and guidance method for construction of reverse logistics system.
In chapter one, background and significance of research paper were stated. Concept of reverse logistics was described. Research state at home and abroad of related fields were summarized. Then main research structure and method were presented.
In chapter two, uncertainty of the system was analyzed and uncertain derived mechanical model of reverse logistics was described. Construction and optimization methodology architecture was researched based on fuzzy theory. Then main factors affecting the number of recycling waste products and recycling time were analyzed based on product life cycle. A fuzzy neural network prediction model of recovery level was presented.
In chapter three, characteristic of common reverse logistics model was compared. Focusing on three types of take-back modes in market with leader of manufacturer, distributor or third-party, corresponding bilevel programming models for each mode under fuzzy environment were set up and then solved in Stackelberg game framework. Taking investment efficiency and risk preference into account, the optimal retail prices, product return rates, wholesale price and profits of channel members of each mode were compared quantatively. Rationality of manufacturer decision was judged from perspective of whole supply chain. In order to ensure relationship in outsourcing mode stable, assignment mechanism of recovery benefit under the contract was designed.
Chapter four described reverse logistics network structure and facilities function. According to liasion with forward logistics network, three kinds of typical network organization structure were analyzed. Taking minimum total operation cost as optimization objective, a common model of network structure was developed. Regarding quantity and demand of returned products and facilities capacity as fuzzy parameters, the proposed model was solved by converting fuzzy chance constraints to their respective crisp equivalents. A new adaptive particle swarm optimization algorithm with dynamically changing inertia weight was brought forward to solve the problem. Then environmental adaptability of network was discussed, and performance robustness index was designed to evaluate network robustness.
Chapter five examined the impact of environmental issues on long-term behaviour of reverse logistics system. The environmental issues examined were environmental protection strategy, remanufacturing capacity expansion strategy and market behavior. Behaviour of system was analyzed through a dynamic simulation model based on the principles of the system dynamics methodology. The dynamic model provided a useful tool, which can be used to evaluate the effect of environmental issues on long-term decision making in collection and remanufacturing activities.
In chapter six, based on forword theoretical studies, demand analysis of reverse logistics information platform was carried on. Structural and functional model of platform was built up.
In chapter seven, main conclusions of this dissertation were summarized and further research issues were put forward.
引文
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