说明：  建立了带约束条件的物流配送问题的数学模型，运用蚁群算法解决物流配送路径 优化问题，并将遗传算法的复制、交叉、变异等遗传算子引入蚁群算法，同时改进信息素的 更新方式、客户点选择策略，以提高算法的收敛速度和全局搜索能力。经过多次实验和计算 ，证明了用改进的蚁群算法优化物流配送线路，可以有效而快速地求得问题的最优解或近似最 优解。
(A mathematical model with the constraints of logistics and distribution issues, the use of ant colony algorithm to solve the problem of logistics distribution route optimization, replication and genetic algorithms, crossover and mutation genetic operators to introduce ant colony algorithm, while improving the way pheromone update customer point selection strategy to improve the convergence speed and global search capability. After several experiments and calculations prove that the optimal solution with improved ant colony algorithm to optimize logistics and distribution lines, can effectively and quickly determined the problem or near optimal solution.)