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    Optimal Allocation of Resources To Meet Transit Fleet Requirements

    Source: Journal of Transportation Engineering, Part A: Systems:;2002:;Volume ( 128 ):;issue: 006
    Author:
    Snehamay Khasnabis
    ,
    Emadeddin Alsaidi
    ,
    Richard Darin Ellis
    DOI: 10.1061/(ASCE)0733-947X(2002)128:6(509)
    Publisher: American Society of Civil Engineers
    Abstract: A two-stage procedure to optimally allocate limited resources for the dual purpose of purchasing new transit buses and rebuilding existing buses is presented in this paper. In stage 1, estimates are derived for the maximum investment that can be justified for rebuilding buses that have fulfilled their service life expectations. In stage 2, optimization by linear programming is used to estimate the number of buses in each category. Two optimization approaches are presented. In approach 1, the objective is to maximize the weighted fleet life, subject to budgetary and demand constraints. In approach 2, the objective is to minimize the total capital investment in the fleet, subject to minimum fleet life and demand constraints. Case studies are presented to demonstrate the application of two approaches. The proposed procedure can be used by state Departments of Transportation to allocate capital dollars among various transit agencies for the dual purpose of purchasing new buses and rebuilding older buses. While it is desirable to replace all the old buses with new ones, budgetary constraints often make it impossible to fund the purchase of all new buses. The proposed approach provides a tool to identify the “next best solution,” a solution that will result in an optimum combination of new and rebuilt buses that will satisfy the requirements of the minimum fleet size as well as the budgetary constraints.
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      Optimal Allocation of Resources To Meet Transit Fleet Requirements

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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorSnehamay Khasnabis
    contributor authorEmadeddin Alsaidi
    contributor authorRichard Darin Ellis
    date accessioned2017-05-08T21:04:11Z
    date available2017-05-08T21:04:11Z
    date copyrightNovember 2002
    date issued2002
    identifier other%28asce%290733-947x%282002%29128%3A6%28509%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/37456
    description abstractA two-stage procedure to optimally allocate limited resources for the dual purpose of purchasing new transit buses and rebuilding existing buses is presented in this paper. In stage 1, estimates are derived for the maximum investment that can be justified for rebuilding buses that have fulfilled their service life expectations. In stage 2, optimization by linear programming is used to estimate the number of buses in each category. Two optimization approaches are presented. In approach 1, the objective is to maximize the weighted fleet life, subject to budgetary and demand constraints. In approach 2, the objective is to minimize the total capital investment in the fleet, subject to minimum fleet life and demand constraints. Case studies are presented to demonstrate the application of two approaches. The proposed procedure can be used by state Departments of Transportation to allocate capital dollars among various transit agencies for the dual purpose of purchasing new buses and rebuilding older buses. While it is desirable to replace all the old buses with new ones, budgetary constraints often make it impossible to fund the purchase of all new buses. The proposed approach provides a tool to identify the “next best solution,” a solution that will result in an optimum combination of new and rebuilt buses that will satisfy the requirements of the minimum fleet size as well as the budgetary constraints.
    publisherAmerican Society of Civil Engineers
    titleOptimal Allocation of Resources To Meet Transit Fleet Requirements
    typeJournal Paper
    journal volume128
    journal issue6
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/(ASCE)0733-947X(2002)128:6(509)
    treeJournal of Transportation Engineering, Part A: Systems:;2002:;Volume ( 128 ):;issue: 006
    contenttypeFulltext
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