Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
Label correcting methods to solve multicriteria shortest path problems
Journal of Optimization Theory and Applications
Computational study of state-of-the-art path-based traffic assignment algorithms
Mathematics and Computers in Simulation
Origin-Based Algorithm for the Traffic Assignment Problem
Transportation Science
Heuristic shortest path algorithms for transportation applications: state of the art
Computers and Operations Research
Reformulating the traffic equilibrium problem via a smooth gap function
Mathematical and Computer Modelling: An International Journal
Hi-index | 0.98 |
The multi-class reliability-based user equilibrium (RUE) problem has been intensively studied in recent years, as it can capture the route choice behaviors of users with heterogeneous risk-aversion under demand and supply uncertainties. Few solution algorithms, however, are available for solving the RUE problems in large-scale road networks. This is mainly due to the non-additive property of the path finding sub-problem in the RUE model. An efficient traffic assignment solution algorithm for solving the multi-class RUE problems in large-scale road networks is proposed in this study. First, an effective shortest path algorithm is developed to explicitly overcome the non-additive difficulty. The algorithm is capable of finding optimal paths for all user classes in one search process and hence the repeated search process for each user class is avoided. This property can save not only computational time but also memory requirement. The proposed shortest path algorithm is then, further incorporated into a path-based traffic assignment algorithm using a column generation technique. Such traffic assignment algorithms can solve the multi-class RUE problem without the requirement of path enumeration. Experimental results show that the proposed solution algorithms can, even for large-scale networks with multi-user classes, efficiently achieve highly accurate RUE solutions within satisfactory computational time.