Using the Genetic Algorithm for Optimization of the Integrated Urban Transportation Systems

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Authors

Sharam Gilani NiaIslamic Azad University of Iran, Rasht Branch, Iran
Bahram SharifIslamic Azad University of Iran, Rasht Branch, Iran
Neda HabibzadehIslamic Azad University of Iran, Rasht Branch, Iran
Musa RezvaniIslamic Azad University of Iran, Rasht Branch, Iran

DOI Number
https://doi.org/https://doi.org/10.15415/jtmge.2011.21006

Keywords
Multi- Demsional Transport, Genetic Algorithms, Pricing, Investment, Regulation

Abstract

Improving the public transportation problems should rely on integrated multidimensional transport policies which can soften the demand of infrastructure investment. However, it would be very difficult to fully consider the multi-dimensional transport polices in planning framework because there would be too many possible policy combinations to be evaluated. So, this study attempts to develop an analytic framework for evaluating urban integrated transport policies comprehensively, including strategies of investment, pricing, management and regulation. To deal with the difficulty of too many policy combinations, genetic algorithms will be used to search for the optimal strategy combination for integrated transport strategy. Finally, the relationship between quantified objectives, policy combinations, and assessment performances would be analyzed using the proposed model.

References

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How to Cite

Sharam Gilani Nia, Bahram Sharif, Neda Habibzadeh, Musa Rezvani. Using the Genetic Algorithm for Optimization of the Integrated Urban Transportation Systems. J.Technol. Manag. Grow. Econ.. 2023, 01, 103-113

Using the Genetic Algorithm for Optimization of the Integrated Urban Transportation Systems

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