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

Authors: Biao-bin Jiang, Han-ming Chen, Li-na Ma, Lei Deng

Addresses: Student Innovation Base of Computer Science and Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China. ' School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China. ' School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, China. ' School of Information Science and Technology, Beijing Institute of Technology, Beijing, 100081, China

Abstract: 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.

Keywords: dynamic traffic routing; ant colony optimisation; ACO; time-dependent pheromones; electrostatic field models; directional angle; simulation; dynamic congestion.

DOI: 10.1504/IJMIC.2011.037826

International Journal of Modelling, Identification and Control, 2011 Vol.12 No.1/2, pp.29 - 35

Published online: 21 Mar 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article