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Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach

机译:公交路线和频率设计:双层建模和混合人工蜂群算法方法

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摘要

This paper proposes a bi-level transit network design problem where the transit routes and frequency settings are determined simultaneously. The upper-level problem is formulated as a mixed integer non-linear program with the objective of minimizing the number of passenger transfers, and the lower-level problem is the transit assignment problem with capacity constraints. A hybrid artificial bee colony (ABC) algorithm is developed to solve the bi-level problem. This algorithm relies on the ABC algorithm to design route structures and a proposed descent direction search method to determine an optimal frequency setting for a given route structure. The descent direction search method is developed by analyzing the optimality conditions of the lower-level problem and using the relationship between the lower- and upper-level objective functions. The step size for updating the frequency setting is determined by solving a linear integer program. To efficiently repair route structures, a node insertion and deletion strategy is proposed based on the average passenger demand for the direct services concerned. To increase the computation speed, a lower bound of the objective value for each route design solution is derived and used in the fitness evaluation of the proposed algorithm. Various experiments are set up to demonstrate the performance of our proposed algorithm and the properties of the problem.
机译:本文提出了一个双层运输网络设计问题,其中运输路线和频率设置是同时确定的。上级问题被表述为混合整数非线性程序,其目的是最大程度地减少乘客中转次数,而下级问题是具有容量约束的公交分配问题。提出了一种混合人工蜂群算法(ABC)来解决双层问题。该算法依靠ABC算法来设计路线结构,并提出一种下降方向搜索方法来确定给定路线结构的最佳频率设置。通过分析下层问题的最优条件并利用下层目标函数和上层目标函数之间的关系来开发下降方向搜索方法。通过求解线性整数程序来确定更新频率设置的步长。为了有效地修复路线结构,基于对相关直接服务的平均乘客需求,提出了节点插入和删除策略。为了提高计算速度,导出了每种路线设计解决方案的目标值下限,并将其用于所提出算法的适应性评估中。建立了各种实验,以证明我们提出的算法的性能和问题的性质。

著录项

  • 作者

    Jiang Y; Szeto WY;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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