用混合整数线性规划表达多类用户均衡

IF 2.1 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Xiao Lin , Ludovic Leclercq , Lóránt Tavasszy , Hans van Lint
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引用次数: 0

摘要

提出了一种用混合整数线性规划(MILP)问题来表述和求解多类用户均衡流量分配的方法。与仿真方法相比,解析式MILP公式使网络分配问题的求解更易于处理。当应用于多类上下文中时,它不需要假设类之间的对称影响,从而允许考虑更丰富的流量行为。此外,它自然地集成在优化问题,如维修计划和交通管理。我们开发了该模型并将其应用于苏福尔斯网络,表明它在较小规模问题上优于传统的基于beckmann和MSA的方法。进一步的研究机会在于开发基于milp的分配的扩展,使用不同的用户均衡或动态分配变体,并改进模型和求解算法以允许大规模应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Formulating multi-class user equilibrium using mixed-integer linear programming

We introduce an approach to formulate and solve the multi-class user equilibrium traffic assignment as a mixed-integer linear programming (MILP) problem. Compared to simulation approaches, the analytical MILP formulation makes the solution of network assignment problems more tractable. When applied in a multi-class context, it obviates the need to assume a symmetrical influence between classes and thereby allows richer traffic behavior to be taken into account. Also, it integrates naturally in optimization problems such as maintenance planning and traffic management. We develop the model and apply it for the Sioux Falls network, showing that it outperforms the traditional Beckmann-based and MSA approaches in smaller-scale problems. Further research opportunities lie in developing extensions of MILP-based assignment, with different variants of user equilibrium or dynamic assignment, and in improving the model and solution algorithms to allow large-scale application.

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来源期刊
CiteScore
4.60
自引率
0.00%
发文量
24
审稿时长
129 days
期刊介绍: The EURO Journal on Transportation and Logistics promotes the use of mathematics in general, and operations research in particular, in the context of transportation and logistics. It is a forum for the presentation of original mathematical models, methodologies and computational results, focussing on advanced applications in transportation and logistics. The journal publishes two types of document: (i) research articles and (ii) tutorials. A research article presents original methodological contributions to the field (e.g. new mathematical models, new algorithms, new simulation techniques). A tutorial provides an introduction to an advanced topic, designed to ease the use of the relevant methodology by researchers and practitioners.
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