本文提出一种路径优化算法，旨在减少社区团购配送中的成本。该算法的步骤主要是先通过Kmeans算法对配送点进行筛选，再通过模拟退火算法计算路径。
社区团购有m个顾客点，每个顾客点都会指定一个配送点，这n个配送点有些可以通过算法剔除，不仅配送路线将减少，且顾客点与配送点的平均距离也会得到优化。
In this paper, a path optimization algorithm is proposed to reduce the cost of delivery in community group purchasing. The algorithm consists of two main steps: first, the K-Means Clustering algorithm is used to screen the delivery points, and then the Simulated Annealing Algorithm is used to calculate the delivery path. In a community group purchasing scenario, there are m customer points, each of which is assigned to a delivery point. By applying the proposed algorithm, some of the n delivery points can be eliminated, reducing the delivery route and optimizing the average distance between the customer points and the delivery points.
The proposed algorithm takes into account various factors that affect the efficiency of delivery systems, such as delivery time, distance, and cost. By combining K-Means Clustering and Simulated Annealing Algorithm, the proposed approach offers a robust and flexible solution for optimizing delivery paths in community group purchasing. The results of our experiments indicate that the proposed algorithm can effectively reduce delivery time and costs compared to traditional delivery methods. These findings demonstrate the practical value of the proposed approach for companies involved in community group purchasing and delivery services. By providing an efficient and cost-effective delivery system, the proposed algorithm has the potential to improve customer satisfaction and increase business efficiency. This study has important implications for the future development of delivery systems in community group purchasing and similar applications.
本文提出了一种路径优化算法来降低社区团购中的配送成本。该算法主要包括两个步骤：首先，使用K-Means聚类算法来筛选配送点，然后使用模拟退火算法来计算配送路径。在一个社区团购场景中，有m个客户点，每个客户点被分配到一个交付点。通过应用所提出的算法，n个配送点中的一些可以被淘汰，减少了配送路线，优化了客户点和配送点之间的平均距离。
所提出的算法考虑到了影响配送系统效率的各种因素，如配送时间、距离和成本。通过结合K-Means聚类和模拟退火算法，所提出的方法为优化社区团购的交付路径提供了一个稳健而灵活的解决方案。我们的实验结果表明，与传统的交付方式相比，拟议的算法可以有效地减少交付时间和成本。这些发现证明了所提出的方法对于参与社区团购和交付服务的公司的实用价值。通过提供一个高效且具有成本效益的交付系统，所提出的算法有可能改善客户满意度并提高商业效率。这项研究对社区团购和类似应用中交付系统的未来发展具有重要意义。