摘 要
随着全球资源环境压力的加剧和循环经济理念的深入推广，逆向物流网络作为实现资源高效回收与再利用的重要途径，其优化布局已成为学术界和产业界关注的核心议题。本研究旨在通过关键节点的优化布局提升逆向物流网络的整体效率与可持续性。为此，本文构建了一个多目标优化模型，综合考虑成本、环境影响和服务水平等多重因素，并引入改进的遗传算法以解决模型复杂性和计算效率之间的矛盾。研究选取某区域废旧电子产品回收网络为案例，通过对比分析不同布局方案的性能表现，验证了模型的有效性和实用性。结果表明，优化后的关键节点布局显著降低了系统总成本，同时提升了资源回收率和网络运行效率。此外，本研究创新性地提出了基于节点重要性评估的动态调整机制，能够灵活应对市场需求变化和政策导向调整。这一机制不仅增强了逆向物流网络的适应能力，还为相关决策提供了科学依据。总体而言，本研究的主要贡献在于将多目标优化理论与实际应用场景相结合，提出了一种兼具理论深度和实践价值的解决方案，为推动逆向物流网络的科学规划与可持续发展提供了重要参考。
关键词：逆向物流网络；多目标优化；关键节点布局；遗传算法；可持续发展
Research on Optimal Layout of Key Nodes in Reverse Logistics Networks
Abstract: With the increasing global pressure on resources and the environment, as well as the deepening promotion of the circular economy concept, the optimization of reverse logistics networks has become a core issue of concern in both academia and industry, as it serves as a critical pathway for achieving efficient resource recovery and reuse. This study aims to enhance the overall efficiency and sustainability of reverse logistics networks through the optimized layout of key nodes. To this end, a multi-ob jective optimization model is developed, integrating multiple factors such as cost, environmental impact, and service level. An improved genetic algorithm is introduced to address the contradiction between model complexity and computational efficiency. A case study of a regional electronic waste recycling network is selected to validate the effectiveness and practicality of the model by comparing the performance of different layout scenarios. The results indicate that the optimized layout of key nodes significantly reduces the total system cost while improving resource recovery rates and network operational efficiency. Furthermore, this study innovatively proposes a dynamic adjustment mechanism based on node importance evaluation, which can flexibly respond to changes in market demand and policy orientation. This mechanism not only enhances the adaptability of reverse logistics networks but also provides scientific support for relevant decision-making. Overall, the primary contribution of this research lies in combining multi-ob jective optimization theory with real-world application scenarios, offering a solution that possesses both theoretical depth and practical value, thus providing significant reference for the scientific planning and sustainable development of reverse logistics networks.
Keywords: Reverse Logistics Network; Multi-ob jective Optimization; Key Node Layout; Genetic Algorithm; Sustainable Development
目 录
一、绪论 1
（一）逆向物流网络研究背景与意义 1
（二）关键节点优化布局的研究现状 1
（三）研究方法与技术路线 2
二、逆向物流网络的关键节点特性分析 2
（一）关键节点的功能定位与作用 2
（二）节点特性的分类与定义 3
（三）影响关键节点布局的主要因素 3
（四）数据驱动的节点特性评估方法 4
三、逆向物流网络中关键节点优化模型构建 4
（一）优化模型的基本框架设计 4
（二）目标函数与约束条件的设定 5
（三）数学建模中的参数选择与处理 5
（四）模型验证与适用性分析 6
（五）不同场景下的模型调整策略 6
四、关键节点优化布局的算法设计与应用 7
（一）常用优化算法的比较与选择 7
（二）遗传算法在节点布局中的应用 7
（三）模拟退火算法的改进与实现 8
（四）实例分析 8
（五）算法性能评价与结果分析 9
结论 9
参考文献 11
致 谢 12
