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The application of variable message sign (VMS) is an important means to relieve traffic congestion. A bi-level programming model is developed to optimize VMS locations considering stochastic user equilibrium (SUE). The upper level model is a planning model that maximizes the utility and minimizes the cost of VMS. The lower level model is a SUE model that is applied to represent route choice behavior under the guidance of VMS. The solution algorithm integrates the method of successive averages (MSA) and an improved genetic algorithm (GA), which searches for the optimal solution. The road segment of Nan’er Huan Road in Xi’an composes the case study. The results show optimal VMS locations considering SUE on sections 10, 12, 14, and 16. The proposed solution algorithm can effectively optimize the study’s multi-objective VMS location problem. The optimal solution has led the results to outperform the operation based on the current VMS layout.
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