基于并行遗传算法的国外空乘繁忙时间智能调度研究

H. Ling
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引用次数: 0

摘要

目前基于智能优化算法的涉外人员智能调度方法通过个体编码实现人员调度,由于目标函数的约束和优化不够全面,导致算法稳定性较低。为此,提出了一种基于并行遗传算法的繁忙时段航空公司外务人员智能调度方法。通过设定人口规模等最优参数,构建以航空公司运营收益和旅客服务度为目标的目标函数,并利用数据的浅拷贝对函数进行优化约束,构建出港航班服务人员调度模型。实验验证了所提智能调度方法的稳定性。实验结果分析表明,该方法构造的目标函数具有高度的收敛性和高度的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Intelligent Scheduling of Foreign Flight Attendants' busy time Based on Parallel Genetic Algorithm
The current intelligent scheduling method of foreign service staff based on intelligent optimization algorithm realizes the scheduling of staff by individual coding, which leads to the low stability of the algorithm because the constraints and optimization of the objective function are not comprehensive enough. In this regard, the intelligent scheduling method of foreign service staff of busy time airlines based on parallel genetic algorithm is proposed. By setting the optimal parameters such as population size, the objective function is constructed with the airline operation revenue and passenger service degree as the objectives, and the shallow copy of data is used to optimize and constrain the function, and the outbound flight service staff scheduling model is constructed. In the experiment, the stability of the proposed intelligent scheduling method is verified. The analysis of the experimental results shows that the objective function constructed by using the proposed method has a high degree of convergence and high stability.
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