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Improved Quantum Artificial Fish Swarm Algorithm For Scheduling Arrival Landing

机译：改进量子人工鱼类群算法调度到达降落

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the task of Aircraft Landing Scheduling (ALS) is to give a landing sequence and landing times for a given set of aircrafts where many constraints must be satisfied, such as safety and utilization rate of the facilities.It built a model for effective scheduling arrival landings based on le objective function is the minimum total delay.This paper proposed an improved quantum artificial fish swarm (IQAF) algorithm for the problem based on artificial fish swarm algorithm (AFSA), lusing the encoding method in quantum evi Intionary algorithm (QEA) and the thought of updating pheromone in ant colony algorithm (ACA). The computational result was compared wi(h firstcomc-first-serve (FCFS) algorithm and artificial fish swarm algorithm (AFSF).Comparative experiments show that the improved quantum artificial fish swarm algorithm is able to obtain an optimal landing sequence rapld! and effectively.
机译：飞机着陆调度（ALS）的任务是为一套给定的飞机提供着陆序列和着陆时间，其中必须满足许多限制，例如设施的安全和利用率。它建立了一个有效的调度到达登陆的模型基于LE目标函数是最小总延迟。本文提出了一种基于人工鱼类群（AFSA）的问题的改进量子人工鱼类群（IQAF）算法，在Quantum EVI IndionArm（QEA）中遏制编码方法蚁群算法（ACA）中信息素更新的思考。计算结果比较了Wi（H FirstComc-First-Sever（FCF）算法和人工鱼类群（AFSF）。采样的实验表明，改进的量子人工鱼类群算法能够获得最佳的着陆序列Rapld！有效。

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