Optimal Rail Transit System Planning Using a Geographic Information System and a Genetic Algorithm

CHRO, AHMED and KHALID, NUR and WASHINGTON, OCHIENG (2016) Optimal Rail Transit System Planning Using a Geographic Information System and a Genetic Algorithm. In: Fourth International Conference on Advances in Civil, Structural and Mechanical Engineering - CSM 2016, 17 - 18 March, 2016, Birmingham City University, Birmingham, UNITED KINGDOM.

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The planning of a rail transit system is a complex process involving the determination of station locations and rail line alignments connecting the stations. There are many requirements and constraints to be considered in the planning process, with complex correlations and interactions, necessitating the application of optimization models in order to realize reliable and cost-effective rail transit systems. Although various optimization models have been developed to solve the rail transit system planning problem, most neglect the complex interactions between station locations and associated rail lines linking them station by treating them in separate optimization processes. This is in addition to focusing mainly on a single objective system requirement and thus resulting in suboptimal solutions. This paper addresses the limitations in the current approaches by developing an optimal planning methodology that treats the rail transit system and its influencing factors in a single integrated process using a geographic information system (GIS) and a genetic algorithm (GA). It accounts for local factors and multiple planning requirements that arise from passenger, operator and community objectives, while optimizing locations of stations and the associated rail line linking the stations simultaneously. The methodology is applied to the City of Leicester (United Kingdom) as a case study to demonstrate its capability for optimal rail transit system planning particularly in regions with complex topographies.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Rail transit system, Rail transit station locations,Rail transit lines, Optimization, Genetic Algorithm, GIS.
Depositing User: Mr. John Steve
Date Deposited: 25 Mar 2019 12:11
Last Modified: 25 Mar 2019 12:11
URI: http://publications.theired.org/id/eprint/887

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