Tabu search algorithm for dynamic vehicle routing problems under real-time information

Dynamic vehicle routing strategies have been widely discussed because of advances in information technologies. Dynamic vehicle routing problems are important aspects of commercial vehicle operation applications of intelligent transportation system technologies. One possible operational benefit of real-time information might be the ability to reroute commercial vehicles efficiently according to current traffic conditions. The present effort is aimed at developing a tabu-based dynamic vehicle routing algorithm under real-time information and then evaluating the algorithm in a simulation-assignment framework. Two types of information, historical information and real-time information, are considered in the tabu search algorithms to design temporal as well as spatial tabu lists for route construction and improvement. Numerical experiments conducted with the network of the city of Taichung, Taiwan, are presented to investigate dynamic vehicle dispatching and routing strategies under real-time information supply strategies and to assess the effectiveness of such strategies for traffic incidents.