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    Rail Transit Route Optimization Model for Rail Infrastructure Planning and Design: Case Study of Saint Andrews, Scotland

    Source: Journal of Transportation Engineering, Part A: Systems:;2014:;Volume ( 140 ):;issue: 001
    Author:
    Min-Wook Kang
    ,
    Manoj K. Jha
    ,
    Ramesh Buddharaju
    DOI: 10.1061/(ASCE)TE.1943-5436.0000445
    Publisher: American Society of Civil Engineers
    Abstract: This paper is aimed at developing a rail transit route optimization model (RTROM) for cost-effective and sustainable rail infrastructure planning and design. Locations of rail transit routes and stations depend on many factors, including potential ridership, costs of land, construction and operation, land use, connecting routes, passenger travel times, and environmental impacts. Suitably located rail transit routes effectively serve the potential demand while also minimizing costs and environmental impacts. Thus, a common problem in all rail infrastructure planning and design projects is to identify the best possible route that satisfies design constraints (such as minimum radius, maximum gradient, and vertical clearance), geographical considerations (such as demand generators and socio-economically sensitive areas) and objectives (such as minimization of associated costs and environmental impacts, or maximization of net benefits). The developed RTROM uses a genetic algorithm for performing optimization, which is integrated to a geographic information system for seamless transfer of land-use, environmental, and topographic data during the optimal search process. The model is tested in a real-world case study from Saint Andrews, Scotland. The lessons learned from the real-world application of the model are discussed. Many extensions of the model remain to be tested in future works.
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      Rail Transit Route Optimization Model for Rail Infrastructure Planning and Design: Case Study of Saint Andrews, Scotland

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    http://yetl.yabesh.ir/yetl1/handle/yetl/69463
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorMin-Wook Kang
    contributor authorManoj K. Jha
    contributor authorRamesh Buddharaju
    date accessioned2017-05-08T22:02:16Z
    date available2017-05-08T22:02:16Z
    date copyrightJanuary 2014
    date issued2014
    identifier other%28asce%29te%2E1943-5436%2E0000489.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/69463
    description abstractThis paper is aimed at developing a rail transit route optimization model (RTROM) for cost-effective and sustainable rail infrastructure planning and design. Locations of rail transit routes and stations depend on many factors, including potential ridership, costs of land, construction and operation, land use, connecting routes, passenger travel times, and environmental impacts. Suitably located rail transit routes effectively serve the potential demand while also minimizing costs and environmental impacts. Thus, a common problem in all rail infrastructure planning and design projects is to identify the best possible route that satisfies design constraints (such as minimum radius, maximum gradient, and vertical clearance), geographical considerations (such as demand generators and socio-economically sensitive areas) and objectives (such as minimization of associated costs and environmental impacts, or maximization of net benefits). The developed RTROM uses a genetic algorithm for performing optimization, which is integrated to a geographic information system for seamless transfer of land-use, environmental, and topographic data during the optimal search process. The model is tested in a real-world case study from Saint Andrews, Scotland. The lessons learned from the real-world application of the model are discussed. Many extensions of the model remain to be tested in future works.
    publisherAmerican Society of Civil Engineers
    titleRail Transit Route Optimization Model for Rail Infrastructure Planning and Design: Case Study of Saint Andrews, Scotland
    typeJournal Paper
    journal volume140
    journal issue1
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/(ASCE)TE.1943-5436.0000445
    treeJournal of Transportation Engineering, Part A: Systems:;2014:;Volume ( 140 ):;issue: 001
    contenttypeFulltext
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