Computation and application of the paired combinatorial logit stochastic user equilibrium problem
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Publication:336886
DOI10.1016/J.COR.2013.08.022zbMath1348.90184OpenAlexW2037938880MaRDI QIDQ336886
Seungkyu Ryu, Anthony Chen, Xiangdong Xu, Keechoo Choi
Publication date: 10 November 2016
Published in: Computers \& Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cor.2013.08.022
partial linearizationtraffic assignmentline searchlogitstochastic user equilibriumpaired combinatorial logit
Games involving graphs (91A43) Case-oriented studies in operations research (90B90) Traffic problems in operations research (90B20)
Related Items (8)
Combined gravity model trip distribution and paired combinatorial logit stochastic user equilibrium problem ⋮ A modified gradient projection algorithm for solving the elastic demand traffic assignment problem ⋮ Constrained Assortment Optimization Under the Paired Combinatorial Logit Model ⋮ Assortment Optimization Under the Paired Combinatorial Logit Model ⋮ Solving the combined modal split and traffic assignment problem with two types of transit impedance function ⋮ A faster path-based algorithm with Barzilai-Borwein step size for solving stochastic traffic equilibrium models ⋮ \textit{Physarum polycephalum} assignment: a new attempt for fuzzy user equilibrium ⋮ Strategy-based transit stochastic user equilibrium model with capacity and number-of-transfers constraints
Uses Software
Cites Work
- Method of successive weighted averages (MSWA) and self-regulated averaging schemes for solving stochastic user equilibrium problem
- A self-adaptive gradient projection algorithm for the nonadditive traffic equilibrium problem
- On the convergence of descent methods for monotone variational inequalities
- Minimization of functions having Lipschitz continuous first partial derivatives
- An algorithm for the equilibrium assignment problem with random link times
- On the Goldstein-Levitin-Polyak gradient projection method
- A Stochastic Approximation Method
- Multidimensional Stochastic Approximation Methods
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