Multilayer Traffic Network Optimized by Multiobjective Genetic Clustering Algorithm

Feng WEN  Mitsuo GEN  Xinjie YU  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E92-A    No.8    pp.2107-2115
Publication Date: 2009/08/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E92.A.2107
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Intelligent Transport System
multilayer network,  route selection,  clustering,  genetic algorithm,  

Full Text: PDF(1.4MB)>>
Buy this Article

This paper introduces a multilayer traffic network model and traffic network clustering method for solving the route selection problem (RSP) in car navigation system (CNS). The purpose of the proposed method is to reduce the computation time of route selection substantially with acceptable loss of accuracy by preprocessing the large size traffic network into new network form. The proposed approach further preprocesses the traffic network than the traditional hierarchical network method by clustering method. The traffic network clustering considers two criteria. We specify a genetic clustering algorithm for traffic network clustering and use NSGA-II for calculating the multiple objective Pareto optimal set. The proposed method can overcome the size limitations when solving route selection in CNS. Solutions provided by the proposed algorithm are compared with the optimal solutions to analyze and quantify the loss of accuracy.