多蚁群协同进化的滑行道调度优化

Multiple ant colony cooperative evolution for optimization of taxiway scheduling

针对当前机场滑行道调度效率较低的问题,提出一种基于协同进化的多蚁群算法。利用蚁群算法在解决复杂的组合优化问题方面的显著优势,在种群内部搜索滑行时间短且没有冲突的路径,在种群间利用蚁群算法良好的协同能力同时进行多个航班的调度,解决滑行的路径搜索问题,实现调度顺序的优化调整。冲突解决是解决滑行道调度问题的关键,采用基于两段锁的思想解决冲突。利用公共数据集对该算法进行验证,实验结果表明了该算法的有效性。

Aiming at the inefficiency problem of taxiway scheduling,a multiple ant colony algorithm based on cooperative evolution was proposed.The ant colony algorithm（ACA）is good at solving the complex combinatorial optimization problem.Taking advantage of this feature,ACA was used for searching routes with the short slide time and without conflicts inside the population.Meanwhile,among the populations,the good synergy of ACA was used for scheduling of multiple flights simultaneously,which not only solved the problem of path search,but achieved the adjustments of scheduling order.Conflict resolution is the key to solving the taxiway scheduling problems,which was resolved with a solution based on two-phase locking.Finally,the algorithm was validated by using the public data sets.The experimental results show that the algorithm is effective.