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多式综合公交系统线网布局优化模型及仿真
引用本文:周高卫,罗 霞.多式综合公交系统线网布局优化模型及仿真[J].计算机应用研究,2013,30(4):1035-1037.
作者姓名:周高卫  罗 霞
作者单位:西南交通大学 交通运输与物流学院, 成都 610031
基金项目:交通运输部西部公交项目(Q024131109010188); 四川省科技计划支撑项目(2011FZ0050)
摘    要:结合综合公交中各式公交的适应性和服务阈值,兼顾出行者不同出行目的时间价值敏感性,建立了综合公交系统线网布局双层优化模型,上层是0-1数学规划模型,下层是用户平衡分配模型。同时,基于改进的IOA进行优化求解,克服了传统单式线网优化层次化不显著的缺陷,提高了布局优化过程求解效率。算例仿真结果表明:综合公交系统需求多样性在客观上决定综合公交系统线网的多元性和层次性,线网布局优化需考虑不同出行目的的时间价值特性,以提升系统速度和能力的连续性。同时,基于改进的IOA在多式综合公交系统线网布局优化的巨大搜索空间中可靠便捷地找到近似最优解,提高了计算效率。

关 键 词:综合公交系统  时间价值  布局优化  双层规划模型  智能优化算法  用户平衡分配模型  0-1数学规划模型

Network layout optimization model of multi-modalcomprehensive public transit system and simulation
ZHOU Gao-wei,LUO Xia.Network layout optimization model of multi-modalcomprehensive public transit system and simulation[J].Application Research of Computers,2013,30(4):1035-1037.
Authors:ZHOU Gao-wei  LUO Xia
Affiliation:School of Transportation & Logistic, Southwest Jiaotong University, Chengdu 610031, China
Abstract:In combination of the different transit mode's adaptability and service threshold of the multi-modal comprehensive public transit system, this paper established the layout bi-level optimization model of comprehensive transit system, giving attention to the time value sensitivity of different trip purposes. The upper model was 0-1 mathematics programming model, while the lower model was the user equilibrium assignment model. Besides, this paper proposed solving algorithm based on the improved IOA, it adopted above algorithm to find solution of model which overcame the defects of lack of significant hierarchy and the consubstantial trend of traditional single mode network optimization and it improved the solving effect as well. Example simulation result shows that the diversity of comprehensive transit system demand objectively determines its network hierarchy and pluralism and the network layout optimization should consider different time value to improve the system speed and capacity continuity. The improved IOA can find the approximate best result in the huge search space of optimization, while greatly increases the computational efficiency.
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