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首页> 外文会议>International conference on education technology and computer >Improved Quantum Artificial Fish Swarm Algorithm For Scheduling Arrival Landing
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Improved Quantum Artificial Fish Swarm Algorithm For Scheduling Arrival Landing

机译：改进的量子人工鱼群调度算法

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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：飞机着陆计划（ALS）的任务是给出必须满足许多约束条件（如设施的安全性和利用率）的给定飞机集的着陆顺序和着陆时间，它建立了有效安排到达着陆的模型针对该问题，本文提出了一种改进的基于人工鱼群算法（AFSA）的量子人工鱼群算法（IQAF）。蚁群算法（ACA）中更新信息素的想法。将计算结果与“先到先得”算法和人工鱼群算法进行了比较。比较实验表明，改进的量子人工鱼群算法能够有效地获得最优着陆序列。

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