The transportation network design problem (NDP) is a high capital investment decision-making problem that inherently involves both subjective and objective uncertainties as well as multiple objectives. Goal programming is a practically useful approach with an explicit consideration of planners’ goal setting and priority structure among the multiple objectives. This paper describes the development of a hybrid goal programming (HGP) approach for modeling both subjective and objective uncertainties simultaneously in the NDP decision-making process. Planners’ subjective uncertainty regarding the linguistic setting of goals and priority structure is characterized as a set of fuzzy variables with nonlinear achievement and satisfaction functions, and the objective travel demand uncertainty is characterized as a set of random variables with predefined probability distributions. The HGP-NDP is formulated as a chance-constrained model in a bi-level programming framework and solved by a genetic algorithm procedure based on random simulation and fuzzy evaluation. The paper provides numerical examples and a real case study to demonstrate the features and applicability of the proposed HGP approach in solving the NDP under an uncertain environment.


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    Titel :

    Stochastic Network Design Problem with Fuzzy Goals


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Xu, Xiangdong (Autor:in) / Chen, Anthony (Autor:in) / Cheng, Lin (Autor:in)


    Erscheinungsdatum :

    01.01.2013




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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