A new binary genetic programming approach to designing public transportation systems according to transit-oriented development criteria

Document Type : Article

Authors

1 Department of Landscape Architecture, Faculty of Architecture and Design, Ataturk University, Erzurum, Turkey

2 - Department of Landscape Architecture, Faculty of Architecture and Design, Ataturk University, Erzurum, Turkey - Faculty of Agriculture, Kirgizstan Turkiye Manas University, Bishkek, Kirgizstan

3 Department of Civil Engineering, Antalya Bilim University, Antalya, Turkey

Abstract

This study introduces a new evolutionary approach called binary genetic programming (BGP) to design and assess public transportation systems from a sustainable development perspective. The BGP combines evolutionary system identification techniques with k-fold cross-validation to obtain an accurate model between the land use and transportation parameters from a sustainable urban development point of view. To assess the new model, two public transportation systems including the new tram line of Antalya (Turkey) and the bus rapid transit line of Bhopal (India) were considered. The model was applied to classify the transportation systems into transit-oriented development (TOD) and non-TOD. The solutions generated by the new model were compared with those of classic decision tree (DT) as well as the state-of-the-art random forest (RF) models evolved as the benchmarks in this study. The results showed that the BGP is highly efficient and may provide less than 5% classification error. It is superior to the DT and RF solutions, which typically require higher datasets to avoid overfitting. Furthermore, the explicit formulation of BGP in combination with the multicriteria evaluation method increases human insight on the factors affecting the design of public transportations from a sustainable urban development point of view.

Keywords

References

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Scientia Iranica
Volume 30, Issue 3
Transactions on Civil Engineering (A)
May and June 2023
Pages 936-951

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History

  • Receive Date: 15 December 2021
  • Revise Date: 12 February 2022
  • Accept Date: 09 May 2022

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