Optimization of Fresh Goods Multi-Center Vehicle Routing Problem Based on Resource Sharing and Temperature Control
2022, 30 (11):
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.
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