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摘要: 从可见度、信息浓度更新、参数对蚁群算法加以改进, 可见度计算利用节约值及距离, 使用较优的数个解完成信息浓度的更新, 根据迭代次数的改变灵活设置的影响系数, 然后引入交换法完成局部搜索, 得到混合算法。用此法对物流配送车辆路径问题进行求解, 寻找最优路径。该方法得到车辆数为5 veh, 配送路径总长为855.68 km, 优于遗传算法的求解结果, 表明该方法可行。Abstract: Ant-colony-system was improved in three aspects, such as visibility, trail update and parameters calculation. Its visibility was calculated according to the saving value and distance, its trail update was connected with several best solutions, its parameters was determined according to the generation. Hybrid algorithm was founded after adding 2-option (2-opt) to finish local search. The algorithm was applied to solve vehicle routing problem, so as to find the best path. Taking 5 vehicles model as an example, its total route is 855.68 km after calculation with the algorithm, its accuracy is better than one of genetic algorithm.
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Key words:
- logistics engineering /
- vehicle routing /
- ant-colony-algorithm /
- hybrid algorithm
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表 1 已知数据
Table 1. Given data
仓库编号 总仓库 1 2 3 4 5 6 坐标值 (52, 4) (15, 49) (0, 61) (51, 15) (25, 71) (38, 62) (35, 45) 需求量 0 1.64 1.31 0.43 3.38 1.13 3.77 仓库编号 7 8 9 10 11 12 13 坐标值 (100, 41) (10, 52) (26, 79) (87, 7) (24, 89) (19, 25) (20, 99) 需求量 3.48 0.39 0.24 1.03 2.35 2.60 1.00 仓库编号 14 15 16 17 18 19 20 坐标值 (73, 91) (100, 95) (7, 73) (69, 86) (24, 3) (66, 14) (9, 30) 需求量 0.65 0.58 2.56 1.27 2.69 3.26 2.97 
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表 2 混合算法计算结果
Table 2. Computation results of hybrid algorithm
计算次序 1 2 3 4 5 6 使用车辆数/veh 5 6 5 5 5 5 配送路径总长/km 856.07 879.84 865.45 863.92 856.20 864.43 计算次序 7 8 9 10 平均值 使用车辆数/veh 5 5 5 6 5.2 配送路径总长/km 863.92 858.10 855.68 870.83 863.44
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