TY  - INPR
ID  - SisLab3609
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3609/
A1  - Nguyen, Thi-Hau
A1  - Do, Trung-Tuan
A1  - Nguyen, Duc-Nhan
A1  - Lu, Dang Nhac
A1  - Nguyen, Ha Nam
Y1  - 2019///
N2  - This paper presents a hybrid method that combines the genetic algorithm (GA) and the ant colony system algorithm (ACS), namely GACS, to solve the traffic routing problem. In the proposed framework, we use the genetic algorithm to optimize the ACS parameters in order to attain the best trips and travelling time through several novel functions to help ants to update the global and local pheromones. The GACS framework is implemented using the VANETsim package and the real city maps from the open street map project. The experimental results show that our framework achieves a considerably higher performance than A-Star and the classical ACS algorithms in terms of the length of the global best path and the time for trips. Moreover, the GACS framework is also efficient in solving the congestion problem by online monitoring the conditions of traffic light systems.
JF  - VNU Journal of Science: Comp. Science & Com. Eng.
TI  - A Hybrid Method Based on Genetic Algorithm and Ant Colony System for Traffic Routing Optimization
AV  - none
ER  -