A heuristic method for a congested capacitated transit assignment model with strategies

被引:20
作者
Codina, Esteve [1 ]
Rosell, Francisca [2 ]
机构
[1] Univ Politecn Cataluna, Stat & Operat Res Dept, Campus Nord,Bldg C5,Off 216 C Jordi Girona,1-3, ES-08034 Barcelona, Spain
[2] Univ Politecn Cataluna, Stat & Operat Res Dept, Campus Nord,Bldg C5,Off 217 C Jordi Girona,1-3, ES-08034 Barcelona, Spain
关键词
Congested transit assignment; Variational inequalities; Strategy-based transit equilibrium; Heuristic methods; FLOW-DEPENDENT COSTS; TRAFFIC ASSIGNMENT; FIXED-POINTS; PASSENGER ASSIGNMENT; USER EQUILIBRIUM; NETWORKS; CONSTRAINTS; SYSTEMS;
D O I
10.1016/j.trb.2017.07.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper addresses the problem of solving the congested transit assignment problem with strict capacities. The model under consideration is the extension made by Cominetti and Correa (2001), for which the only solution method capable of resolving large transit networks is the one proposed by Cepeda et al. (2006). This transit assignment model was recently formulated by the authors as both a variational inequality problem and a fixed point inclusion problem. As a consequence of these results, this paper proposes an algorithm for solving the congested transit assignment problem with strict line capacities. The proposed method consists of using an MSA-based heuristic for finding a solution for the fixed point inclusion formulation. Additionally, it offers the advantage of always obtaining capacity-feasible flows with equal computational performance in cases of moderate congestion and with greater computational performance in cases of highly congested networks. A set of computational tests on realistic small- and large-scale transit networks under various congestion levels are reported, and the characteristics of the proposed method are analyzed. (C) 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页码:293 / 320
页数:28
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