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Origin-destination-based truncated quadratic programming algorithm for traffic assignment problem
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DOI：10.1080/19427867.2016.1227531.png)
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Abstract
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The solution of the static traffic assignment problem (TAP) with fixed origin-destination (OD) demands is considered. The original Frank and Wolfe (FW) algorithm is the most widely used in practice while suffering from a sublinear rate of convergence. The OD-based FW (ODBFW) algorithm was an attempt to speed up its convergence. The FW algorithm has been also used to compute search directions by partially solving a sequence of quadratic programming (QP) subproblems in a truncated QP (TQP) framework (FWTQP). In this study, we introduce an OD-based FWTQP (ODFWTQP) algorithm by embedding the decomposition and column generation in the FWTQP algorithm. The convergence rate of the ODFWTQP is investigated on the Chicago and Philadelphia test networks. A direct comparison is done between the proposed ODFWTQP and the algorithms of FW, ODBFW, FWTQP and the origin-based algorithm (OBA). Another direct comparison with a current commercial projected gradient (PG) algorithm is also provided. Based on the numerical results, the proposed algorithm shows a surprising performance.
Keywords:
Traffic assignment
truncated quadratic programming
algorithms
path-based formulation
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