基于资源共享和温度控制的生鲜商品多中心车辆路径优化问题

针对生鲜商品多中心共同配送优化研究在资源共享和温度控制有效结合方面存在的不足，提出研究集成资源共享和温度控制的生鲜商品多中心车辆路径优化问题。首先，结合生鲜商品的易腐性和配送过程的及时性特征，构建了包含生鲜商品多中心间的运输成本、配送成本、车辆温控成本、违反时间窗惩罚成本、生鲜商品价值损失和车辆租赁成本的物流运营成本最小和配送车辆使用数最小的双目标优化模型。然后，设计了结合生鲜需求客户地理位置、需求商品温控区间和时间窗约束的K-means多维聚类算法，进而提出一种TS-NSGA-II算法，该算法设计了禁忌搜索算法(TS)和非支配排序遗传算法(NSGA-II)间有效的选择性赋予机制，进而增强了解空间的搜索和寻优能力，并通过与MOGEA和MOPSO算法的对比分析，进一步验证了模型和TS-NSGA-II算法的有效性。最后，通过实例分析探讨了不同资源共享模式和温控区间的多中心车辆路径优化方案，研究结果可为生鲜商品物流配送企业进行资源共享模式选择和温控区间设计提供方法支撑和决策支持。

Optimization of Fresh Goods Multi-Center Vehicle Routing Problem Based on Resource Sharing and Temperature Control

Due to the characteristics of perishability, timeliness and temperature control heterogeneity of fresh goods, as well as customers’ diversified demands for fresh goods, scattered geographical locations, and high time window requirements, the logistics distribution requirements of fresh goods are significantly higher than those of other commodities. However, due to the limited distribution resources of fresh goods, it is impossible to realize the whole process of low-temperature transportation and distribution of fresh goods, and the non-low-temperature transportation and distribution processes will lead to serious value loss of fresh goods over time, which will limit the development of fresh goods logistics industry. The resource sharing and cooperation among fresh goods logistics facilities can realize the rational allocation and time-sharing use of resources among multiple fresh goods logistics distribution facilities, thus improving the efficiency of resource utilization. To overcome the shortcomings of the fresh goods multi-center joint distribution optimization study in the effective combination of resource sharing and temperature control, and then the fresh goods multi-center vehicle routing optimization problem with integrated resource sharing and temperature control is proposed. A bi-objective optimization model is constructed, including the minimum logistics distribution cost and the minimum number of vehicles in fresh goods distribution with the resource sharing and temperature control constraints. A TS-NSGA-II hybrid algorithm based on K-means multi-dimensional clustering is devised to address the model, and an effective selective endowing mechanism between the tabu search (TS) and the nondominated sorting genetic algorithm II (NSGA-II) is proposed to enhance the search and optimization ability of the solution space. Through the comparison and analysis with MOGEA and MOPSO algorithms, the effectiveness of the proposed model and TS-NSGA-II algorithm is further verified. Finally, through a case study, five resource sharing modes are compared and discussed, includingnon-sharing and unreasonable temperature control, internal sharing and unreasonable temperature control, global sharing and unreasonable temperature control, internal sharing and reasonable temperature control, and global sharing and reasonable temperature control. The research results show that the global sharing and reasonable temperature control mode can effectively reduce the value loss of fresh goods, temperature control cost, and the number of fresh vehicles, and then reduce the total operating cost of fresh logistics distribution network.This paper will enrich the multi-center distribution network optimization model of fresh goods, and then provide a new theoretical basis and decision support for the selection of resource sharing modes and the design of temperature control ranges for fresh goods logistics distribution enterprises.