eprintid: 3609
rev_number: 4
eprint_status: archive
userid: 283
dir: disk0/00/00/36/09
datestamp: 2019-11-27 13:41:20
lastmod: 2019-11-27 13:41:20
status_changed: 2019-11-27 13:41:20
type: article
succeeds: 3608
metadata_visibility: no_search
creators_name: Nguyen, Thi-Hau
creators_name: Do, Trung-Tuan
creators_name: Nguyen, Duc-Nhan
creators_name: Lu, Dang Nhac
creators_name: Nguyen, Ha Nam
creators_id: nguyenhau@vnu.edu.vn
creators_id: namnh@vnu.edu.vn
title: A Hybrid Method Based on Genetic Algorithm and Ant Colony System for Traffic Routing Optimization
ispublished: inpress
subjects: IT
divisions: fac_fit
abstract: 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.
date: 2019
full_text_status: none
publication: VNU Journal of Science: Comp. Science & Com. Eng.
refereed: FALSE
projects: QG 17.39
citation:   Nguyen, Thi-Hau and Do, Trung-Tuan and Nguyen, Duc-Nhan and Lu, Dang Nhac and Nguyen, Ha Nam  (2019) A Hybrid Method Based on Genetic Algorithm and Ant Colony System for Traffic Routing Optimization.  VNU Journal of Science: Comp. Science & Com. Eng. .       (In Press)