An evolutionary approach to traffic assignment

A. Bazzan, Daniel Cagara, B. Scheuermann
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引用次数: 17

Abstract

Traffic assignment is an important stage in traffic modeling. Most of the existing approaches are based on finding an approximate solution to the user equilibrium or to the system optimum, which can be computationally expensive. In this paper we use a genetic algorithm to compute an approximate solution (routes for the trips) that seeks to minimize the average travel time. To illustrate this approach, a non-trivial network is used, departing from binary route choice scenarios. Our result shows that the proposed approach is able to find low travel times, without the need of recomputing shortest paths iteratively.
交通分配的进化方法
交通分配是交通建模的一个重要阶段。现有的大多数方法都是基于寻找用户平衡或系统最优的近似解,这可能是计算昂贵的。在本文中,我们使用遗传算法来计算一个近似解(行程路线),寻求最小化平均旅行时间。为了说明这种方法,使用了一个非平凡网络,脱离了二进制路由选择场景。研究结果表明,该方法能够在不需要迭代计算最短路径的情况下,找到较短的行程时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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