Time-dependent pheromones and electric-field model: a new ACO algorithm for dynamic traffic routing

In this paper, we present a dynamic ant colony optimisation (ACO) algorithm to solve dynamic traffic routing problem. The main objective of this work is to search out the least-time-cost route in a variable-edge-weight graph. We introduce time-dependent pheromones and electric-field model as two heuristic factors to improve the basic ACO. The simulation results show that the proposed dynamic ACO algorithm can effectively reduce time cost by avoiding the dynamic congestion areas. Finally, this proposed heuristic algorithm is verified to be steady-going by repeated testing.