An evolutionary approach for finding optimal automatic vehicle identification reader locations in transportation networks

Author

Chen, Anthony ; Chootinan, Piya ; Pravinvongvuth, Surachet

Author_Institution

Utah State Univ., Logan, UT, USA

Volume

1

fYear

2004

fDate

19-23 June 2004

Firstpage

181

Abstract

A modified distance-based genetic algorithm is proposed to solve the multi-objective automatic vehicle identification (AVI) reader location problem studied in this paper. The objectives are: (1) minimizing the number of AVI readers, (2) maximizing the coverage of origin-destination (O-D) pairs, and (3) maximizing the number of AVI readings. These three objectives are strategically designed to catch the maximum number of trips covering the maximum number of AVI readers. In order to study the trade-off among the three objectives, non-dominated solutions are retained and analyzed. The results show that there is a trade-off between the quality (measured by objectives 2 and 3) and cost (measured by objective 1) of coverage.

Keywords

automobiles; genetic algorithms; image recognition; image sensors; minimisation; traffic engineering computing; AVI reader minimization; coverage maximization; distance-based genetic algorithm; evolutionary approach; multiobjective automatic vehicle identification; optimal automatic vehicle identification reader locations; origin-destination pairs; transportation networks; Costs; Data mining; Genetic algorithms; Intelligent networks; Licenses; Surveillance; Telecommunication traffic; Transponders; Transportation; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2004. CEC2004. Congress on

Print_ISBN

0-7803-8515-2

Type

conf

DOI

10.1109/CEC.2004.1330855

Filename

1330855