中文摘要：

摘要：针对带有时间窗限制的旅行商问题（travelling salesman problem with time windows，TSPTW）提出了一种基于磁场模型的蚁群变异算法（MFM—ACOMF）．它通过修正传统蚁群算法的启发函数，满足用户的时间需求，并降低算法陷入局部最优的可能性；在得到最终解后，通过变异策略对未达到时间窗标准的顾客节点进行优化．仿真实验结果表明：MFM—ACOMF算法与传统ACOM算法相比，在最优解质量和顾客满意率方面都有一定程度的提高．

英文摘要：

To aim at the travelling salesman problem with time windows （TSPTW）, an ant colony optimization algorithm with Mutation Features based on Magnetic Field （MFM-ACOMF） was put forward. It improved the heuristic function in the traditional ant colony optimization （ACO） algorithm, to meet the time requirement of customers and reduce the probability of getting a local optimal. Moreover, when it obtained the preliminary solution after all the iterations, a mutation strategy was used to optimize the customer nodes that did not reach the time window limit. The simulation results show that the MFM- ACOMF algorithm has certain improvement on both the optimal solution quality and customer satisfaction, compared with the AC0 algorithm.