Please use this identifier to cite or link to this item: https://doi.org/10.1061/(ASCE)0733-947X(2010)136:1(52)
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dc.titleOrigin-based partial linearization method for the stochastic user equilibrium traffic assignment problem
dc.contributor.authorLee, D.-H.
dc.contributor.authorMeng, Q.
dc.contributor.authorDeng, W.
dc.date.accessioned2014-06-17T08:22:34Z
dc.date.available2014-06-17T08:22:34Z
dc.date.issued2010-01
dc.identifier.citationLee, D.-H., Meng, Q., Deng, W. (2010-01). Origin-based partial linearization method for the stochastic user equilibrium traffic assignment problem. Journal of Transportation Engineering 136 (1) : 52-60. ScholarBank@NUS Repository. https://doi.org/10.1061/(ASCE)0733-947X(2010)136:1(52)
dc.identifier.issn0733947X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/65955
dc.description.abstractThis paper proposes a modified origin-based partial linearization method for solving the logit-based stochastic user equilibrium traffic assignment problem formulated by a strictly convex minimization model in terms of origin-based link flows. As a feasible descent direction method, it first generates a feasible descent direction in terms of the origin-based link flows by Bell's second logit-based stochastic network loading algorithm without path enumeration, and it proceeds to improve the descent direction according to the Fukushima's strategy and the PARTAN technique which haven been successfully applied to accelerate convergence of the link-based Frank-Wolfe method for solving the deterministic user equilibrium traffic assignment problem. To tackle the numerical overflow or underflow issue of the exponential function calculation arising in the computerized logit-based stochastic network loading algorithms, this paper develops a scientific notation based engineering approach for large-scale problems. Two numerical examples are carried out to compare the proposed solution method with the conventional origin-based partial linearization method and the method of successive averages in computational time and accuracy of solution. © 2010 ASCE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1061/(ASCE)0733-947X(2010)136:1(52)
dc.sourceScopus
dc.subjectAlgorithms
dc.subjectMathematical models
dc.subjectTraffic assignment
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1061/(ASCE)0733-947X(2010)136:1(52)
dc.description.sourcetitleJournal of Transportation Engineering
dc.description.volume136
dc.description.issue1
dc.description.page52-60
dc.identifier.isiut000273614500007
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