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Mathematical Modeling for Optimizing Skip-Stop Rail Transit Operation Strategy Using Genetic Algorithm

机译：基于遗传算法优化防滑轨道交通运行策略的数学建模

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This research developed an optimization model using a Genetic Algorithm that coordinated the stopping stations for skip-stop rail operation. Using the flexibility of the Genetic Algorithm, this model included many realistic conditions, such as different access modes, different stopping scenarios, different collision constraints, different objective functions, and etc. For this research, the Seoul Metro systems line No. 4 was used as an example. With skip-stop operation, total travel time became about 17-20 percent shorter than with original all-stop operation, depending on the stopping constraints. In-vehicle travel time became about 20-26 percent shorter due to skipping stations, although waiting, transfer, and additional access times increased by 24-38 percent.

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