Optimal routing in freeway networks via sequential linear programming

Based on the Ant Colony Optimization (ACO) algorithm, we previously developed an optimization method to solve the dynamic traffic routing problem in freeway networks, called Ant Colony Routing (ACR). By using Model Predictive Control (MPC), we can iteratively apply ACR at each control step to generate a control signal - i.e. splitting rates at each node in the traffic network. Motivated by the MPC framework with ACR, we show in this paper that sequential linear programming (SLP) can be used as optimization method for solving the dynamic traffic routing problem in some specific cases, resulting a lower computation time while achieving a similar performance as the ACR algorithm.