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Use of Fuzzy Optimization and Linear Goal Programming Approaches in Urban Bus Lines Organization

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Soft Computing in Industrial Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 223))

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Abstract

Determination of bus stop locations and bus stop frequencies are important issues in public transportation planning. This study analyzes the relationships among demand, travel time, bus stop locations, frequency, fleet size and passenger capacity parameters and develops models for bus stop locations and bus service frequency using fuzzy linear programming and linear goal programming approaches. The models are microscopic and applied to determine the bus stop locations and bus service frequency in the city of Izmir, Turkey, where 26 bus routes pass through two stops in the center city. The fuzzy optimization model minimizes the passenger access time and in-vehicle travel time. The reduction of the values of the bus service frequency and time parameters derived by the two proposed models are validated by a cost function. Encouraging results are obtained.

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References

  1. Chien, S.I., Qina, Z.: Optimization of bus stop locations for improving transit accessibility. Trans. Plann. Technol. 27(3), 211–227 (2004)

    Article  Google Scholar 

  2. Furth, P., Rahbee, A.: Optimal bus stop spacing through dynamic programming and geographic modeling. Trans. Res. Rec. 1731, 15–22 (2000)

    Google Scholar 

  3. Saka, A.A.: Model for determining optimum bus-stop spacing in urban areas. J. Trans. Eng. 127(3), 195–199 (2001)

    Google Scholar 

  4. Dell’Olio, L., et al.: A model of cost optimization for the location of bus-stop. In: 16th Mini–EURO Conference and 10th Meeting of EWGT (2005)

    Google Scholar 

  5. LeBlanc, L.J.: Transit system network design. Trans. Res. 22, 383–390 (1988)

    Article  MathSciNet  Google Scholar 

  6. Wirasinghe, S.C.: Initial planning for urban transit systems. In: Advanced Modeling for Transit Operations and Service Planning, pp. 1–29. Elsevier Science, Oxford, (2003)

    Google Scholar 

  7. Alp, S.: The use of linear goal programming approach for bus transit systems, Istanbul Ticaret University. Sci. J. 1(13), 73–91 (2008)

    Google Scholar 

  8. Guihaire, V., Hao, J.K.: Transit network design and scheduling: a global review. Trans. Res. A 42A(10), 1251–1273 (2008)

    Google Scholar 

  9. Chien, S., Yang, Z., Hou, E.: Genetic algorithm approach for transit route planning and design. J. Trans. Eng. 127(3), 200–207 (2001)

    Google Scholar 

  10. Caggiani, L., Ottomanelli, M.: Traffic equilibrium network design problem under uncertain constraints. Procedia-Soc. Behav. Sci. 20, 372–380 (2011)

    Article  Google Scholar 

  11. Murray, A.: A coverage model for improving public transit system accessibility and expanding access. Annu. Oper. Res. 123(1), 143–156 (2003)

    Article  MATH  Google Scholar 

  12. Van Nes, R., Bovy, P.H.: Importance of objectives in urban transit-network design. Trans. Res. Rec. 1735, 25–34 (2000)

    Google Scholar 

  13. Furth, P.G., Wilson, W.H.M.: Setting frequencies on bus routes: theory and practice. Trans. Res. Rec. 818, 1–7 (1981)

    Google Scholar 

  14. Murat Y.S., Kikuchi, S.: The fuzzy optimization approach: a comparison with the classical optimization approach using the problem of timing a traffic signal. Trans. Res. Rec. 2024, 82–91 (Washington D.C) (2007)

    Google Scholar 

  15. Uludağ, N.: Modeling bus lines using fuzzy optimization and linear goal programming approaches. PhD Thesis, Pamukkale University, Denizli, p. 112 (2010)

    Google Scholar 

  16. Murat, Y.S., Uludag, N.: Route choice modelling in urban transportation networks using fuzzy logic and logistic regression methods. J. Sci. Ind. Res. 67(1), 19–27 (2008)

    Google Scholar 

  17. Kikuchi, S.: Treatment of uncertainty in transportation analysis. Virginia Polytechnic Institute and State University, Falls Church, Lecture Notes (2006)

    Google Scholar 

  18. İzmir UAP İzmir Transportation Master Plan-ESHOT Report. İzmir (2010)

    Google Scholar 

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Acknowledgments

This study is dedicated to Prof. Shinya Kikuchi (from Virginia Politechnic Institute and State University) who inspired many researches (including this work) on application of soft computing in transportation.

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Authors and Affiliations

  1. Faculty of Engineering, Pamukkale University, Denizli, Turkey

    Yetis Sazi Murat & Sabit Kutluhan

  2. Yorum Building and Construction Inc., İstanbul, Turkey

    Nurcan Uludag

Authors
  1. Yetis Sazi Murat
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  2. Sabit Kutluhan
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  3. Nurcan Uludag
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Corresponding author

Correspondence to Yetis Sazi Murat .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VŠB-TUO Faculty of Electrical Eng. & Comp. Sci., Ostrava-Poruba, Czech Republic

    Václav Snášel

  2. Department of Computer Science, VŠB-TUO Faculty of Electrical Eng. & Comp. Sci., Ostrava-Poruba, Czech Republic

    Pavel Krömer

  3. Network Design and Research Center, Kyushu Institute of Technology, Fukuoka, Japan

    Mario Köppen

  4. Department of Computer Science, Loughborough University, Lougborough, United Kingdom

    Gerald Schaefer

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Murat, Y.S., Kutluhan, S., Uludag, N. (2014). Use of Fuzzy Optimization and Linear Goal Programming Approaches in Urban Bus Lines Organization. In: Snášel, V., Krömer, P., Köppen, M., Schaefer, G. (eds) Soft Computing in Industrial Applications. Advances in Intelligent Systems and Computing, vol 223. Springer, Cham. https://doi.org/10.1007/978-3-319-00930-8_33

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  • DOI: https://doi.org/10.1007/978-3-319-00930-8_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00929-2

  • Online ISBN: 978-3-319-00930-8

  • eBook Packages: EngineeringEngineering (R0)

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