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    Bus Network Scheduling with Genetic Algorithms and Simulation

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    No. of downloads: 2153

    Date
    2005-05-02
    Author
    Park, Seong Jae
    Advisor
    Schonfeld, Paul M
    Chang, Gang-Len
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    Abstract
    This thesis investigates the costs associated with a bus scheduling problem in an urban transit network for both deterministic and stochastic arrival processes and proposes computerized models for each. A simple genetic algorithm (SGA) with some problem-specific genetic operators is developed for the deterministic arrival process and a simulation-based genetic algorithm (SBGA) is developed for the stochastic arrival process. The new models are applied to an artificial bus network to test their efficiency. Several sensitivity analyses and a goodness test are conducted for each arrival process. The results show that the SGA model can find the optimized solution very quickly when it uses problem-specific operators such as the coordinated headway generator, coordinated headway crossover and coordinated headway mutation. They also show that the SBGA model can find a good solution even though it uses general genetic operators.
    URI
    http://hdl.handle.net/1903/2496
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