基于聚类-遗传算法的物流配送路径优化研究

Research on Logistics Distribution Path Optimization Based on Clustering Genetic Algorithm

为了提高配送效率,需要更好地规划配送路线,通过建立配送路径最优化模型,使用聚类-遗传算法对其求得配送路径的最优解,聚类-遗传算法采用新的染色体编码方式和交叉原则,相较传统遗传算法,迭代收敛速度更快,且呈现出更优的结果,使得区域配送路径路线最短、成本最低。

In order to improve the distribution efficiency,it is necessary to better plan the distribution route,establish the distribution path optimization model,and use the clustering-genetic algorithm to obtain the optimal solution of the distribution path.The clustering-genetic algorithm adopts a new chromosome coding method and crossover principle.Compared with the traditional genetic algorithm,the iterative convergence speed is faster,and the results are better,making the regional distribution route shortest and the cost lowest.