期刊文献+

改进TS算法的助航灯光站人员管理优化方法

An Optimization Method of Personnel Management for Navigation Lighting Station Based on Improved Tabu Search Algorithm
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摘要 为了解决助航灯光站在人员管理方面存在的对灯光设备损伤情况的确认与修复能力低下以及修复情况反馈不及时等问题,提出了一种改进禁忌搜索方法。此方法以禁忌搜索为基础,并且引入了惩罚权重以及多领域分析组合的方法进行优化提高,其中权重可根据具体情况进行动态调整。通过已知资料进行建模,并且设置了多种可能存在的排班情况,以扩大样本空间。通过实例分析,得到在最符合实际的情况下,本文研究方法的加权有效效率值为82.23%,相比于整体规划法的74.69%以及变领域禁忌算法的77.27%分别提高了7.54%和4.96%。本文的研究对提高助航灯光站人员管理有一定的借鉴意义。 In order to solve the problems existing in the personnel management of the navigation lighting station,such as the low recognition and repair ability of the light equipment damage,and the delayed feedback of the repair situation,an improved tabu search method is proposed.This method is based on tabu search,introducing the method of penalty weight and multi-domain analysis combination to improve the optimization,in which the weight can be dynamically adjusted according to the specific situation.Firstly,the known data are used for modeling,and a variety of possible scheduling conditions are set to expand the sample space.Then,the case study shows that the weighted efficiency of the research method is 82.23%in the most practical case,which is 7.54%and 4.96%higher than 74.69%of the overall planning method and 77.27%of the tabu algorithm.Therefore,this study is of certain reference significance for improving the personnel management of navigation lighting station.
作者 于之靖 王科平 郑建文 陶永奎 李鑫 刘志东 YU Zhijing;WANG Keping;ZHENG Jianwen;TAO Yongkui;LI Xin;LIU Zhidong(College of Electronic Information and Automation;College of Aeronautical Engineering,Civil Aviation University of China,Tianjin 300300,China;Automobile&Rail Transportation School,Tianjin Sino-German University of Applied Sciences,Tianjin 300350,China)
出处 《工业工程》 北大核心 2019年第4期1-6,48,共7页 Industrial Engineering Journal
基金 国家自然科学基金委员会与中国民用航空局联合资助项目(U1533111) 中央高校基本科研业务费资助项目(ZYGX2018039) 天津市自然科学基金资助项目(17JCTPJC50700)
关键词 助航灯光站人员管理 改进禁忌搜索 惩罚权重 多领域分析 排班管理 personnel management of navigation lighting station improved tabu search penalty weight multi-domain analysis scheduling management
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