A Bilevel Model For Optimizing Station
Locations Along A Rail Transit Line
Author(s)
S. Samanta & M. K. Jha
Abstract
The population growth and increase in number of commuters in urban areas give
rise to the need to either build or extend a rail transit system requiring: (i)
optimization of the alignment of a rail transit line and (ii) optimization of station
locations along rail transit lines. The positions of the stations depend on many
factors, such as total cost for locating them, proximity from the residential
neighborhoods, feasibility studies, and environmental, and political factors. In
this paper a bilevel programming approach, which minimizes the total cost, is
proposed to solve the station location problem. At the lower level, the potential
ridership generated from the major cities or CBDs are estimated by dividing the
study area in optimum number of zones, to maximize the usage by the potential
riders. At the upper level, the number and location of intermediate stations are
determined by minimizing the sum of user, operator, and location costs. The
primary components of costs are the costs associated with traveling to the station
and in-vehicle travel time, land-acquisition cost (also known as right-of-way
cost), and cost of operating the train, construction of stations and parking
facilities. The total cost is minimized using a Genetic Algorithm (GA). A
Geographic Information System (GIS) is used in order to work directly with
maps of the proposed rail-line, existing road networks and transit lines, and land
and property boundaries. The population and passenger distribution in the study
area as well as the travel times are obtained using a GIS which is integrated to
the GA, to obtain the best station locations. The model is applied to decide on the
optimum positions of stations along a transit corridor of an artificial case study.
The results indicate that one can optimally locate station locations with improved
precision if GIS data with sufficient accuracy were available.
Keywords: bilevel programming, rail transit station location, genetic algorithm.
Keywords
bilevel programming, rail transit station location, genetic algorithm.
Related Book
Other papers in this volume
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