配送路径的选择直接影响着物流配送成本的构成且占有较大比例，合理规划配送路线能够有效提升客户满意度的同时并降低相关企业的配送成本。本文针对某公司配送中心满足客户需求时的配送路径进行优化，将各个需求点加载相应的需求量和时间窗后，建立客户满意度和配送成本函数，最终结合低碳、时间窗、客户满意度、成本等因素得出配送路径的多目标优化模型。使用遗传算法进行求解，结果表明该模型能够达到预期效果并显著降低了配送中心在配送过程中的成本，具有一定的实际指导意义。
The choice of distribution path directly affects the composition of logistics distribution costs and occupies a large proportion. Proper planning of distribution routes can effectively improve customer satisfaction and reduce the distribution costs of related companies. This paper optimizes the distribution path when a company’s distribution center meets customer needs, loads each demand point with the corresponding demand and time window, establishes customer satisfaction and distribution cost functions, and finally combines low carbon, time window, and customer satisfaction, cost and other factors to build the multi-objective optimization model of the distribution path. Using genetic algorithm to solve, the results show that the model can achieve the expected effect and significantly reduce the cost of the distribution center in the distribution process, which has certain practical guiding significance.
References
[1]
Piecyk, M.I. and Mckinnon, A.C. (2010) Forecasting the Carbon Foot-Print of Road Freight Transport in 2020. Interna-tional Journal of Production Economics, 128, 31-42. https://doi.org/10.1016/j.ijpe.2009.08.027
[2]
Solomon, M.M. (1986) On the Worst-Case Performance of some Heuristics for the Vehicle Routing and Scheduling Problem with Time Window Constraints. Networks, 16, 61-174. https://doi.org/10.1002/net.3230160205
[3]
Ombuko, B., Nakamura, M. and Osamu, M. (2002) A Hybrid Search Based on Genetic Algorithm and Tabu Search for Vehicle Rout-ing. 6th International Conference on Artificial Intelligence and Soft Computing, Banff, 17-19 July 2002, 176-181.
