A heuristic method for a congested capacitated transit assignment model with strategies - Codina, Esteve; Rosell, Francisca (Transportation research. Part B: methodological, 2017)
•The capacitated congested strategy-based transit assignment is solved using an MSA method as result of its VI reformulation.•At each iteration a capacitated linear problem is solved using Lagrangian relaxation, generating the hyperpaths of the solution.•Solutions are always capacity feasible, even under very high demand levels.•The method behaves better and is computationally as efficient as the one in Cepeda et al. (2001), in any congestion level.•Passenger delay models at stops, derivated from queueing theory, with infinite delays, can be integrated. 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.