Continuous Transportation Network Design Problem Based on Bi-level Programming Model

Abstract

A bi-level programming model was widely used to describe the continuous transportation network design problem. The objective function in upper-level model was to make the sum of total impedance and total investment budget minimal in a traffic network. The lower-level model was a user equilibrium assignment model with fixed demand. In order to make the results more realistic, this paper proposed an improved model with stochastic transportation network design, and presented genetic algorithm and Frank-Wolfe (FW) algorithm to find optimal solution. Then a specific network example was given to prove the effectiveness of the model. The results show that an optimal value of existing links capacities for the formulation can be obtained and it can minimize the sum of total impedance and investment budget, which can provide a reasonable reference for the decision-makers.