Airline fleet assignment involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of an agent-based integer optimization algorithm to a "cold start" fleet assignment problem. Results show that the optimizer can successfully solve such highly- constrained problems (129 variables, 184 constraints).


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    Titel :

    Fleet Assignment Using Collective Intelligence


    Beteiligte:

    Erscheinungsdatum :

    2004-01-01


    Medientyp :

    Sonstige


    Format :

    Keine Angabe


    Sprache :

    Englisch




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