研究车辆路径调度优化问题。在车辆调度中存在多种路径选择问题，按路径优劣区分，当调度车辆存在多种选择时，根据调度结果得出的优劣区分度较小，使路径调度存在随机性问题。传统的方法在解决调度随机性问题时，由于选择过多，造成收敛速度慢，精确度不高，容易陷入局部最优的困境。提出了一种基于蚁群和循环博弈的车辆路径调度算法，采用蚁群和循环博弈混合进行优化，增强了蚁群算法和循环博弈算法各自的性能，提高了总体算法的寻优性能。实验结果说明，改进算法能够有效处理时间窗的车辆路径调度问题，获取的物流配送优化结果明显优于传统算法，解决了传统算法过早收敛的问题，具有重要的应用价值。%Vehicle routing optimal scheduling problem with time Windows is a combinatorial optimization prob-lem. In the construction of vehicle routing problem with time Windows, on the basis of mathematical model, the au-thor proposed a vehicle routing algorithm based on ant colony and circular game scheduling algorithm. The algorithm adopted ant colony and circular game mix optimization, improved ant colony algorithm and circular game algorithm performance, and enhanced the overall performance of optimization algorithm. The experiment result shows that the algorithm can efficiently solve the problem of premature convergence of traditional algorithm, and has important appli-cation value.
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