A multiple-path gradient projection method for solving the logit-based stochastic user equilibrium model
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...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Minnesota Libraries Publishing
2020-11-01
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| Series: | Journal of Transport and Land Use |
| Subjects: | |
| Online Access: | https://www.jtlu.org/index.php/jtlu/article/view/1600 |
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| Summary: | 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. |
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| ISSN: | 1938-7849 |