[1]姚锦宝,姚宝珍,尹智宏,等.基于双种群遗传算法的公交线路发车间隔优化[J].深圳大学学报理工版,2012,29(No.6(471-580)):559-564.[doi:10.3724/SP.J.1249.2012.06559]
　YAO Jin-bao,YAO Bao-zhen,YIN Zhi-hong,et al.A bus headway optimization model with dual-population genetic algorithm[J].Journal of Shenzhen University Science and Engineering,2012,29(No.6(471-580)):559-564.[doi:10.3724/SP.J.1249.2012.06559]
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基于双种群遗传算法的公交线路发车间隔优化()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第29卷
期数:
2012年No.6(471-580)
页码:
559-564
栏目:
交通物流
出版日期:
2012-11-30

文章信息/Info

Title:
A bus headway optimization model with dual-population genetic algorithm
文章编号:
20120616
作者:
姚锦宝1; 姚宝珍2; 尹智宏3; 于滨4
1) 北京交通大学土木建筑工程学院，北京 100044；2) 大连理工大学汽车工程学院，辽宁 大连 116024
3) 内蒙古锡乌铁路有限责任公司，内蒙古 锡林浩特 026000；4) 大连海事大学交通运输管理学院，辽宁 大连 116026
Author(s):
1) School of Civil Engineering & Architecture, Beijing Jiaotong University, Beijing 100044, P.R.China
2) School of Automotive Engineering, Dalian University of Technology, Dalian 116024, Liaoning Province, P.R.China
3) Inner Mongolia Xiwu Railway Co. Ltd., Xilinhot 026000, Inner Mongolia Autonomous Region, P.R.China
4) Transportation Management College, Dalian Maritime University, Dalian 116026, Liaoning Province, P.R.China
关键词:
公交线路; 发车间隔; 双种群; 遗传算法; 公交调度; 系统优化
Keywords:
bus line;  bus headway;  dual-population;  genetic algorithm;  bus dispatching;  system optimization
分类号:
U 491.1
DOI:
10.3724/SP.J.1249.2012.06559
文献标志码:
A
摘要:
提出一个公交线路发车间隔优化模型，以公交系统的社会总效益最大化为目标，兼顾乘客和运营者双方利益，设计公交网络中各条线路的发车间隔．该模型在车辆资源不变的约束下，通过线性加权法衡量乘客和运营者的利益，以达到系统最优目的．为求解该模型，开发了一个双种群的遗传算法，该算法可有效保持遗传算法进化过程中的多样性，提高优化质量．以大连市主城区公交系统的数据对该模型和算法进行检验，结果表明，若整合大连市公交车辆资源，可改善整个系统的服务水平，且降低系统总成本.
Abstract:
A model for bus headway optimization is presented, aiming to minimize the overall cost of passengers and the bus operator, considering the vehicle fleet constrain. The cost the parties concerned can be measured by a linear weighted technique. A dual-population genetic algorithm is proposed to solve the headway optimization model. This model can keep the diversity of this algorithm during its evolution, which will greatly improve the performance of the genetic algorithm. Finally, data collected in Dalian city, China, are used to verify the model and algorithm. Results show that reasonable resource assessment can improve the service quality and decrease the cost of the transit system.

参考文献/References:

［1］ Scheele S. A supply model for public transit services［J］. Transportation Research: B, 1980,14: 133-146.
［2］ Sun C J, Zhou W, Wang Y Q. Scheduling combination and headway optimization of bus rapid transit［J］. Journal of Transportation Systems Engineering and Information Technology, 2008,8(5): 61-67.
［3］ Tom V M, Mohan S. Transit route network design using frequency coded genetic algorithm［J］. J Transp Een-asce, 2003,129(2): 186-195.
［4］ Park S J. Bus Network Scheduling with Genetic Algorithms and Simulation［D］. Maryland(USA): University of Maryland, 2005.
［5］ YANG Zhao-sheng. Theory and Method of Urban Intelligent Public Transportation System［M］. Beijing: Railway Press, 2002: 56-76.( in Chinese)
杨兆升.城市智能公共交通系统理论与方法［M］.北京：中国铁道出版社，2002：56-76.
［6］ SONG Rui, HE Shi-wei, YANG Hai, et al. Optimal transit operation plan model and algorithm with stochastic OD demands ［J］. China Civil Engineering Journal, 2006, 39(4):110-115.(in Chinese)
宋瑞, 何世伟, 杨海, 等. 基于随机需求的公交运营设计优化模型及算法［J］.土木工程学报，2006，39(4):110-115.
［7］ YU Bin, YANG Zhong-zhen, CHENG Chun-tian, et al. Bi-level programming model for optimizing bus frequencies and its algorithm［J］. Journal of Jilin University ：Engineering and Technology Edition, 2006, 36(5): 664-668.(in Chinese)
于滨, 杨忠振, 程春田, 等. 公交线路发车频率优化的双层规划模型及其解法［J］.吉林大学学报工学版,2006, 36(5):664-668.
［8］ CAI Liang-wei，HU Shi-xi.A genetic algorithm based on similarity and its application on JSP［J］. Journal of Shenzhen University Science and Engineering, 2006,23(2):107-111.(in Chinese)
蔡良伟，胡世曦. 基于相似性遗传算法及其在JSP中的应用［J］.深圳大学学报理工版, 2006,23(2):107-111.
［9］ WU Xu-yi, WU Xiao-yu. Improved genetic algorithm for job-shop scheduling［J］. Journal of Shenzhen University Science and Engineering,2006,23(3):272-277.(in Chinese)
吴序一, 伍晓宇. 非量产模式下车间调度的改进遗传算法［J］.深圳大学学报理工版,2006,23(3):272-277.
［10］ Zhao G H, Shen W H, Wu M L. Ultra-wideband antenna design using FDTD and double population genetic algorithm［J］. Microwave and Optical Technology Letters, 2009, 51(2): 361-364.
［11］ Holland J H. Adaptation in Natural and Artificial Systems［M］. Michigan(USA): University of Michigan Press, 1975: 234-245.
［12］ LI Bi, LIN Tu-sheng. Modified genetic algorithm based on competitive coevolution［J］. Journal of Shenzhen University Science and Engineering, 2009,26(1):24-29.(in Chinese)
李碧,林土胜.基于竞争协同进化的改进遗传算法［J］. 深圳大学学报理工版,2009,26(1):24-29.
［13］ CAI Liang-wei . Real-coded adaptive genetic annealing algorithm based on distance measurement［J］. Journal of Shenzhen University Science and Engineering, 2004,21(4):291-294.(in Chinese)
蔡良伟. 基于距离测度的实数编码自适应遗传退火算法［J］. 深圳大学学报理工版, 2004,21(4):291-294.

备注/Memo

备注/Memo:
Received：2010-04-27；Revised：2012-02-15；Accepted：2012-08-20
Foundation：National Natural Science Foundation of China（51208079, 51108053）
Corresponding author：Dr. YAO Bao-zhen. E-mail: yaobaozhen@yahoo.cn
Citation：YAO Jin-bao, YAO Bao-zhen, YIN Zhi-hong, et al. A bus headway optimization model with dual-population genetic algorithm ［J］. Journal of Shenzhen University Science and Engineering, 2012, 29(6): 559-564.（in Chinese）
基金项目：国家自然科学基金资助项目（51208079, 51108053）
作者简介：姚锦宝（1972-），男（汉族），安徽省安庆市人，北京交通大学讲师、博士. E-mail: jbyao@bjtu.edu.cn
引文：姚锦宝，姚宝珍，尹智宏，等. 基于双种群遗传算法的公交线路发车间隔优化［J］. 深圳大学学报理工版，2012，29（6）：559-564.
更新日期/Last Update: 2012-11-30