A multiple-path gradient projection method for solving the logit-based stochastic user equilibrium model

2Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

This paper proposes a path-based algorithm for solving the well-known logit-based stochastic user equilibrium (SUE) problem in transportation planning and management. Based on the gradient projection (GP) method, the new algorithm incorporates a novel multiple-path gradient approach to generate the descent direction in consideration of many paths existing in every single origin-destination (O-D) pair. To apply the path-based algorithm, the SUE problem is reformulated as a variational inequality (VI), and a working path set is predetermined. The numerical experiments are conducted on the Winnipeg network where a large number of paths are provided. The results show the multiple-path gradient projection algorithm outperforms the original GP method. Three different step size strategies, including the fixed step size, self-regulated averaging and self-adaptive Armijo’s strategies, are involved to draw a more general conclusion. Also, the effects of the path number on computational performance are analyzed. The multiple-path gradient projection (MGP) method converges much faster than the GP method when the path set size gets large.

Cite

CITATION STYLE

APA

Tan, H., Du, M., & Yu, C. B. (2020). A multiple-path gradient projection method for solving the logit-based stochastic user equilibrium model. Journal of Transport and Land Use, 13(1), 539–558. https://doi.org/10.5198/jtlu.2020.1600

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free