Computational study of state-of-the-art path-based traffic assignment algorithms
Mathematics and Computers in Simulation
An Efficient Method to Compute Traffic Assignment Problems with Elastic Demands
Transportation Science
A self-adaptive gradient projection algorithm for the nonadditive traffic equilibrium problem
Computers and Operations Research
Computation and application of the paired combinatorial logit stochastic user equilibrium problem
Computers and Operations Research
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This paper develops a path-based traffic assignment algorithm for solving the elastic demand traffic assignment problem (EDTAP). A modified path-based gradient projection (GP) method combined with a column generation is suggested for solving the equivalent excess-demand reformulation of the problem in which the elastic demand problem is reformulated as a fixed demand problem through an appropriate modification of network representation. Numerical results using a set of real transportation networks are provided to demonstrate the efficiency of the modified GP algorithm for solving the excess-demand formulation of the EDTAP. In addition, a sensitivity analysis is conducted to examine the effects of the scaling parameter used in the elastic demand function on the estimated total demand, number of generated paths, number of used paths, and computational efforts of the modified GP algorithm.