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    Transit Route Network Design Using Parallel Genetic Algorithm

    Source: Journal of Computing in Civil Engineering:;2004:;Volume ( 018 ):;issue: 003
    Author:
    Jitendra Agrawal
    ,
    Tom V. Mathew
    DOI: 10.1061/(ASCE)0887-3801(2004)18:3(248)
    Publisher: American Society of Civil Engineers
    Abstract: A transit route network design (TRND) problem for urban bus operation involves the determination of a set of transit routes and the associated frequencies that achieve the desired objective. This can be formulated as an optimization problem of minimizing the total system cost, which is the sum of the operating cost and the generalized travel cost. A review of previous approaches to solve this problem reveals the deficiency of conventional optimization techniques and the suitability of genetic algorithm (GA) based models to handle such combinatorial optimization problems. Since GAs are computationally intensive optimization techniques, their application to large and complex problems is limited. The computational performance of a GA model can be improved by exploiting its inherent parallel nature. Accordingly, two parallel genetic algorithm (PGA) models are proposed in this study. The first is a
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      Transit Route Network Design Using Parallel Genetic Algorithm

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    http://yetl.yabesh.ir/yetl1/handle/yetl/43180
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    contributor authorJitendra Agrawal
    contributor authorTom V. Mathew
    date accessioned2017-05-08T21:13:06Z
    date available2017-05-08T21:13:06Z
    date copyrightJuly 2004
    date issued2004
    identifier other%28asce%290887-3801%282004%2918%3A3%28248%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/43180
    description abstractA transit route network design (TRND) problem for urban bus operation involves the determination of a set of transit routes and the associated frequencies that achieve the desired objective. This can be formulated as an optimization problem of minimizing the total system cost, which is the sum of the operating cost and the generalized travel cost. A review of previous approaches to solve this problem reveals the deficiency of conventional optimization techniques and the suitability of genetic algorithm (GA) based models to handle such combinatorial optimization problems. Since GAs are computationally intensive optimization techniques, their application to large and complex problems is limited. The computational performance of a GA model can be improved by exploiting its inherent parallel nature. Accordingly, two parallel genetic algorithm (PGA) models are proposed in this study. The first is a
    publisherAmerican Society of Civil Engineers
    titleTransit Route Network Design Using Parallel Genetic Algorithm
    typeJournal Paper
    journal volume18
    journal issue3
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)0887-3801(2004)18:3(248)
    treeJournal of Computing in Civil Engineering:;2004:;Volume ( 018 ):;issue: 003
    contenttypeFulltext
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