Abstract
The optimization model is framed with a goal to minimize overall consumption of travel time for passengers. A variety of constrains are considered, including time, capacity, stop number, profit and so on. According to the features of the model, the hill-climbing algorithm is adopted to obtain the initial solution, which reduces the time of optimization. Meanwhile, direct order encoding method, namely node method, is introduced for encoding, construct a Hybrid Genetic Algorithm for the solution. The results show that adapter value is more steady and the model result is preferable when the variation rate is increased while the number of iteration is decreased.
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