This paper utilizes the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with an elite strategy for multi-objective optimization of bus timetables. In this study, three optimization objectives - passenger travel time, bus operation cost, and bus resource efficiency - are common and conflicting goals in optimizing bus route services. The algorithm’s findings indicate that the optimized timetable leads to a 10.2% reduction in passenger travel time, a 4% decrease in public transportation operating costs, and an 8.4% reduction in the index of public transport resource efficiency, thereby achieving partial optimization of the objectives. This notable improvement demonstrates the potential of multi-objective optimization methods in bus operation management.


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    Title :

    Departure timetable optimization based on NSGA-II


    Contributors:

    Conference:

    Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024) ; 2024 ; Guilin, China


    Published in:

    Proc. SPIE ; 13251


    Publication date :

    2024-08-28





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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