改进蚁群算法的航空物流运输路径规划仿真

Simulation of Air Logistics Route Planning Based on Improved Ant Colony Algorithm

在航空物流运输中,由于受恶劣天气等因素影响,导致航空运输路径出现航线重复,造成运输距离过长、配送效率降低等问题。为了解决上述问题,提出考虑多因素耦合的航空物流运输路径规划方法。通过对航空物流运输路径建模分析,获得运输影响条件,设定目标函数。在多种条件约束下,采用实时优化蚁群算法获取模型最优解,实现航空物流运输路径规划。实验结果表明,所提方法的航空物流运输路径规划时间在10ms以内、航程短、危险度低,说明该方法性能高,能够节约成本。

At present,bad weather and other factors may cause duplication of air transportation routes,resulting in long transportation distances and low distribution efficiency.In order to solve these problems,a method of planning air logistics transportation path considering multi-factor coupling was proposed.Based on the modeling analysis of air logistics transportation path,the transportation impact conditions were obtained.Meanwhile,the objective function was set.Under a variety of constraints,the real-time optimization ant colony algorithm was adopted to obtain the optimal solution of the model,thus achieving the air logistics transportation path planning.Experimental results show that the transportation path planning time of the method is less than 10ms,and the flying range is short.The risk is also low.Therefore,the method has high performance and can save costs.