United States Department of Transportation
i
Mathematical modeling for optimizing skip-stop rail transit operation strategy using genetic algorithm.
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2012-03-01
[PDF-987.36 KB]
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Abstract:"With skip-stop rail transit operation, transit agencies can reduce their operating costs and fleet size,
and passengers can experience reduced in-transit travel times without extra track and technological
improvement. However, since skip-stop operation does not serve all the stations, passengers at
exclusive stopping stations can possibly experience increased access time, waiting time, total travel
time, and transfer. Only when the stopping stations are carefully coordinated can skip-stop services
benefit passengers and transit agencies.
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 system’s 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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