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

Anthony Chen, Piya Chootinan, Surachet Pravinvongvuth

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)


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 O-D pairs with the minimum 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.
Original languageEnglish
Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Number of pages7
Publication statusPublished - 13 Sep 2004
Externally publishedYes
EventProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States
Duration: 19 Jun 200423 Jun 2004


ConferenceProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Country/TerritoryUnited States
CityPortland, OR

ASJC Scopus subject areas

  • Engineering(all)

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