改进自适应遗传算法解决登机桥桥手调度问题

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英文篇名：Solution to boarding bridge operator scheduling problem based on improved adaptive genetic algorithm 作者：丁芳 ; 杨创 ; 关山度 ; 陈桂波 英文作者：Ding Fang;Yang Chuang;Guan ShANDu;Chen Guibo;College of Electronic Information and Automation,Civil Aviation University of China;Baiyun Airport Ground Equipment Co.,Ltd.Ground Service Department,Guangzhou City Guangdong Province; 关键词：改进自适应遗传算法 ; 登机桥桥手调度 ; 适应度函数 ; 调度原则 英文关键词：improved adaptive genetic algorithm;;boarding bridge operator scheduling;;fitness function;;scheduling principle 中文刊名：NJLG 英文刊名：Journal of Nanjing University of Science and Technology 机构：中国民航大学电子信息与自动化学院;白云机场地面设备有限公司地勤部门; 出版日期：2019-03-13 13:23 出版单位：南京理工大学学报 年：2019 期：v.43;No.224 基金：中央高校基本科研业务费项目中国民航大学资助专项(3122017003) 语种：中文; 页：NJLG201901013 页数：7 CN：01 ISSN：32-1397/N 分类号：98-104

摘要

为了降低因登机桥桥手调度问题而引起的机场运行秩序被破坏、登机桥桥手工作效率低下以及工作负载不平衡事件发生的可能性,该文通过改进自适应遗传算法结合登机桥桥手调度原则对调度问题进行建模求解。首先设计了有针对性的适应度函数。同时为了克服传统遗传算法无法直接应用于该问题以及改进算法性能,该文改进了算法的执行流程,最终通过改进后的算法对问题进行优化计算。通过算法计算得到了满意的调度结果,并且与基本遗传算法、传统改进自适应遗传算法以及模拟退火遗传算法进行比较,发现性能得到大幅度提升。算法不仅避免了未改进之前的早熟问题,同时加快了收敛速度以及人工调度带来的隐患,同时克服了传统遗传算法无法直接适用于登机桥桥手调度的问题,为机场地勤部门对于桥手调度问题提供了工具和方法,具有重要实际意义与工程应用价值。
        In order to reduce the probability of the disruption of airport operation order,inefficiency and unbalanced workload caused by boarding bridge operator scheduling problem,an improved adaptive genetic algorithm combined with the scheduling principle is used to model and solve the scheduling problem. The corresponding fitness function is designed according to the problems. In order to overcome the problem that the traditional genetic algorithm can not be directly applied to the problem and can not improve the performance,the execution process of the algorithm is improved according to the characteristics of the scheduling problem. Finally,the improved algorithm is used to optimize the calculation of the problem. Satisfactory results are obtained through the improved algorithm calculation,and compared with the basic genetic algorithm,traditional improved adaptive genetic algorithm(AGA) and simulated annealing genetic algorithm,it is found that the performance is greatly improved. The improved algorithm can not only avoid the premature problem and the hidden danger of manual scheduling,but also accelerate convergence speed. It overcomes the problem that the traditional genetic algorithm can not be directly applied to the scheduling problem of boarding bridge drivers,and provides the airport ground service department tools and methods for scheduling problem,and has important practical significance and engineering application value.

引文

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