A new approach to future land use and transportation planning for high-growth cities is presented. The approach employs a genetic algorithm to efficiently search through hundreds of thousands of possible future plans. A new fitness function is developed to guide the genetic algorithm toward a Pareto set of plans for the multiple competing objectives that are involved. This set may be placed before decision makers. A Pareto set scanner also is described that assists decision makers in shopping through the Pareto set to select a plan. Some of the differences between simultaneous planning and separate planning of highly coupled twin cities also are examined.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Land Use and Transportation Planning for Twin Cities Using a Genetic Algorithm


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Balling, Richard J. (Autor:in) / Taber, John (Autor:in) / Day, Kirsten (Autor:in) / Wilson, Scott (Autor:in)


    Erscheinungsdatum :

    2000-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Land Use and Transportation Planning for Twin Cities Using a Genetic Algorithm

    Balling, R. J. / Taber, J. / Day, K. et al. | British Library Conference Proceedings | 2000



    Municipal Land-Use/Transportation Planning with a Genetic Algorithm

    Balling, R. J. / Taber, J. T. / Brown, M. R. et al. | British Library Conference Proceedings | 1998



    Regional Land Use and Transportation Planning with a Genetic Algorithm

    Balling, Richard / Lowry, Michael / Saito, Mitsuru | Transportation Research Record | 2003