|Table of Contents|

Solution to boarding bridge operator scheduling problembased on improved adaptive genetic algorithm(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2019年01期
Page:
94-
Research Field:
Publishing date:

Info

Title:
Solution to boarding bridge operator scheduling problembased on improved adaptive genetic algorithm
Author(s):
Ding Fang1Yang Chuang1Guan Shandu2Chen Guibo2
1.College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China; 2.Baiyun Airport Ground Equipment Co.,Ltd. Ground Service Department,Guangzhou CityGuangdong Province,Guangzhou 510000,China
Keywords:
improved adaptive genetic algorithm boarding bridge operator scheduling fitness function scheduling principle
PACS:
TP18
DOI:
10.14177/j.cnki.32-1397n.2019.43.01.013
Abstract:
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.

References:

[1] Hong W H,Kim J Y,Lee C M,et al. Energy consumption and the power saving potential of a university in Korea:Using a field survey[J]. Journal of Asian Architecture & Building Engineering,2011,10(2):445-452.
[2]Sait H H. Auditing and analysis of energy consumption of an educational building in hot and humid area[J]. Energy Conversion & Management,2013,66(2):143-152.
[3]Yarbrough I,Sun Q,Reeves D C,et al. Visualizing building energy demand for building peak energy analysis[J]. Energy & Buildings,2015,91:10-15.
[4]Min H C,Rhee E K. Potential opportunities for energy conservation in existing buildings on university campus:A field survey in Korea[J]. Energy & Buildings,2014,78(4):176-182.
[5]Altan H,Douglas J S,Kim Y K. Energy performance analysis of university buildings:Case studies at Sheffield University,UK[J]. Architectural Engineering Technology,2014,3(29):2.
[6]Zhou X,Yan J,Zhu J,et al. Survey of energy consumption and energy conservation measures for colleges and universities in Guangdong province[J]. Energy & Buildings,2013,66:112-118.
[7]赵超,林思铭,许巧玲. 基于GM-RBF神经网络的高校建筑能耗预测[J]. 南京理工大学学报,2014,38(1):48-53.
Zhao Chao,Lin Siming,Xu Qiaoling. College building energy consumption prediction based on GM-RBF neural network[J]. Journal of Nanjing University of Science and Technology,2014,38(1):48-53.
[8]赵美,于航,石磊,等. 上海某高校学院楼基于能耗审计结果的节能潜力分析[J]. 建筑节能,2017(4):100-104.
Zhao Mei,Yu Hang,Shi Lei,et al. Energy-saving potential analysis of a college building in Shanghai based on the results of energy consumption audit[J]. Building Energy Efficiency,2017(4):100-104.
[9]Guan J,Nord N,Chen S. Energy planning of university campus building complex:Energy usage and coincidental analysis of individual buildings with a case study[J]. Energy & Buildings,2016,124:99-111.

[10]徐斌. 中国低碳校园建设-复旦大学案例分析[D]. 上海:复旦大学环境科学与工程系,2011.
[11]Dascalaki E G,Sermpetzoglou V G. Energy perfor-mance and indoor environmental quality in Hellenic schools[J]. Energy & Buildings,2011,43(2-3):718-727.
[12]高彪,谭洪卫,宋亚超. 高校校园建筑用能现状及存在问题分析——以长三角地区某综合型大学为例[J]. 建筑节能,2011,39(2):41-44.
Gao Biao,Tan Hongwei,Song Yachao. Analysis of the current situation and problems of energy consumption in colleges and universities-Taking a comprehensive university in the Yangtze River Delta as an example[J]. Building Energy Efficiency,2011,39(2):41-44.
[13]吴成霞. 天津市工业能耗预测与节能评价研究[D]. 天津:天津理工大学经济与管理学院,2013.
[14]Jiang Ping. A low carbon sustainable strategy using CDM methodological approach to large commercial buildings in Beijing and Shanghai[D]. East Anglia:University of East Anglia,2009.

Memo

Memo:
-
Last Update: 2019-02-28