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In order to design the traffic network more accurately, the bi-level programming model for the continuous net- work design problem based on the paired combinatorial Logit stochastic user equilibrium model is proposed in this study. In the model, the paired combinatorial Logit stochastic user equilibrium model which is used to characterize the route choice behaviors of the users is adopted in the lower level model, and the minimum summation of the system total costs and investment amounts is used in the upper objective function. The route-based self-regulated averaging (SRA) algo- rithm is designed to solve the stochastic user equilibrium model and the genetic algorithm (GA) is designed to get the op- timal solution of the upper objective function. The effectiveness of the proposed combining algorithm which contains GA and SRA is verified by using a simple numerical example. The solutions of the bi-level models which use the paired combinatorial Logit stochastic user equilibrium model in the lower level model with different demand levels are com- pared. Finally, the impact of the dispersion coefficient parameter which influences the decision results of the network de- sign problem is analyzed.

Continuous Network Design Based on the Paired Combinatorial Logit Stochastic User Equilibrium Model