为了集中资源发展自身核心竞争力，生产型企业将越来越多的物流服务任务 外包给专业的第三方、第四方物流服务公司。这些物流企业面对快速增长的市场 规模和日益激烈的行业竞争，如何在一定的成本约束条件下尽可能地满足顾客日 渐丰富的服务需求成为提升竞争力的关键。基于此，越来越多的物流企业尝试将 制造业中“大规模定制（Mass Customization，简记为MC）”的思想应用到物流 服务业中，以期利用规模效应降低物流服务成本的同时，为顾客提供更加多元化、 个性化的物流服务内容。本文将以此为研究背景，具体研究了大规模定制物流服 务过程中的以下问题。 首先，基于大规模定制物流服务模式的特点，提出了基于两阶段模糊质量功 能展开（Quality Function Deployment，简记为QFD）的物流服务质量评估方法。 针对大规模定制服务模式的特点以及物流服务评估过程中存在的主观性和模糊 性，本文提出了一种在大规模定制物流服务模式下基于两阶段Fuzzy QFD的物 流服务绩效评估方法。通过质量屋（House Of Quality，简记为HOQ）计算出当 服务集成商设置不同的顾客订单解耦点位置时的各项评估指标的得分情况，然后 构建了一个物流服务质量评估函数和“优质服务”模糊集，从而可以直观判断出 当解耦点位于不同位置时的物流服务质量。 第二，针对大规模定制物流服务模式下确定顾客订单解耦点（Customer Order Decoupling Point，简记为CODP）过程中存在的主观性和模糊性等问题，提出了 一种基于模糊规划模型的CODP定位方法。在该模型中，以物流服务集成商利润 最大化为目标，以“优质物流服务”和“满意交付时间”为模糊约束条件，兼顾 了CODP定位过程中的定性指标和定量指标，为物流服务供应链CODP的研究 提供了新思路。 第三，针对大规模定制物流服务过程中物流服务提供商选择和物流订单分配 问题，本文构建了一个联合优化决策模型来同时确定提供商选择方案和订单分配 方案。该联合决策模型是一个典型的多目标混合整数非线性规划模型，为此本文 提出了一种基于两层编码技术的改进遗传算法来求解该模型。在该模型中，本文 同时考虑了顾客企业、物流服务集成商以及众多功能型物流服务提供商的满意度， 力求所提出的服务提供商选择和订单分配联合决策方案能使得物流服务供应链 中主要成员的满意度达到最大。 第四，本文建立了大规模定制物流服务模式下不同子程序服务商选择和订单 分配的非线性混合整数多目标优化模型。采用定量的方法同时确定最优供应商选 III 择策略、订单分配策略和最优CODP位置。采用不同的方法将多目标规划模型转 化为单目标规划模型，并设计了一种基于多层编码技术的改进遗传算法对模型进 行求解。通过数值案例验证了算法的有效性，通过灵敏度分析得到一些重要的管 理学启示。 综上所述，本文将大规模定制模式的应用领域拓展到物流服务行业中，并具 体研究了大规模定制物流服务模式下的服务质量评估问题、CODP定位问题、服 务提供商选择和订单分配联合优化问题，并分别建立了相应的数学模型，设计了 求解算法。本文的研究丰富了服务业实行大规模定制模式的理论研究成果，为物 流企业提供了新的思路和决策依据。 关键词：大规模定制；物流服务供应链；绩效评估；CODP；提供商选择； 订单分配；遗传算法 IV ABSTRACT In order to concentrate resources and develop their own core competitiveness, production-oriented enterprises outsource more and more logistics service tasks to professional third-party and fourth party logistics service companies. Faced with the rapid growth of market scale and increasingly fierce industry competition, how to meet the increasingly rich service needs of customers under certain cost constraints has become the key to enhance competitiveness. Based on this, more and more logistics companies try to apply the idea of “Mass Customization (MC)” in the manufacturing industry to the logistics service industry, in order to use the effect of scale to reduce the cost of logistics services, and at the same time provide more diversified and personalized logistics services for customers. Based on this background, this paper studies the following problems in the process of mass customization logistics service. First, based on the characteristics of mass customization logistics service model, a logistics service quality evaluation method based on two-stage fuzzy QFD is proposed. In view of the characteristics of mass customization service mode and the subjectivity and fuzziness in the process of logistics service evaluation, this paper proposes a logistics service performance evaluation method based on Two-stage Fuzzy QFD under mass customization logistics service mode. Based on the house of quality (HOQ), this paper calculates the scores of each evaluation index when the service integrator sets different customer order decoupling points, and then constructs a logistics service quality evaluation function and "quality service" fuzzy set, which can directly determine the logistics service quality when the decoupling points are located in different positions. Secondly, aiming at the problems of subjectivity and fuzziness in the process of determining customer order decoupling point (CODP) under the mode of mass customization logistics service, a CODP positioning method based on fuzzy programming model is proposed. In this model, the goal is to maximize the profit of logistics service integrators, the fuzzy constraints are "high quality logistics service" and "satisfactory delivery time", the qualitative and quantitative indexes in the process of CODP positioning are considered, which provides a new idea for the research of CODP positioning of logistics service supply chain. Thirdly, aiming at the problem of logistics service provider selection and logistics V order allocation in the process of mass customization logistics service, this paper constructs a joint optimization decision-making model to determine the provider selection scheme and order allocation scheme at the same time. The joint decision model is a typical multi-objective mixed integer nonlinear programming model, so this paper proposes an improved genetic algorithm based on two-layer coding technology to solve the model. In this model, we consider the satisfaction of customer enterprises, logistics service integrators and many functional logistics service providers at the same time, and strive to make the proposed joint decision-making scheme of service provider selection and order allocation to maximize the satisfaction of the main members of the logistics service supply chain. Fourth, this paper establishes a nonlinear mixed integer multi-objective optimization model for the selection and order allocation of different subprogram service providers under the mode of mass customization logistics service. The quantitative method is used to determine the optimal supplier selection strategy, order allocation strategy and optimal CODP location. Different methods are used to transform multi-objective programming model into single objective programming model, and an improved genetic algorithm based on multi-layer coding technology is designed to solve the model. The effectiveness of the algorithm is verified by numerical examples, and some important management implications are obtained by sensitivity analysis. To sum up, this paper extends the application field of mass customization mode to logistics service industry, and specifically studies the service quality evaluation, CODP positioning, service provider selection and order allocation joint optimization under mass customization logistics service mode, and establishes corresponding mathematical models and designs the solution algorithm. The research of this paper enriches the theoretical research results of implementing mass customization mode in service industry, and provides new ideas and decision-making basis for logistics enterprises. KEYWORDS: Mass customization; Logistics service supply chain; Performance evaluation; CODP; Supplier selection; order allocation; Genetic algorithm VI 目 录 第一章 绪论............. 1 1.1 研究背景.... 1 1.2 研究必要性与研究意义........... 2 1.3 国内外研究现状....................... 3 1.3.1 大规模定制与顾客订单解耦点................... 3 1.3.2 物流服务供应链与物流服务大规模定制... 5 1.3.3 提供商选择和订单分配 6 1.3.4 研究评述........................ 7 1.4 研究内容、创新点和结构安排.............................. 7 1.4.1 主要研究内容................ 7 1.4.2 主要创新点.................... 8 1.4.3 结构安排........................ 9 第二章 基于两阶段模糊QFD的大规模定制物流服务供应链绩效评估...... 11 2.