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A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area

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  • Mohsen Momenitabar

    (Department of Transportation, Logistics, and Finance, North Dakota State University, Fargo, ND 58105-6050, USA)

  • Jeremy Mattson

    (Upper Great Plains Transportation Institute, North Dakota State University, NDSU Dept. 2880, Fargo, ND 58105-6050, USA)

Abstract

In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers.

Suggested Citation

  • Mohsen Momenitabar & Jeremy Mattson, 2021. "A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area," Sustainability, MDPI, vol. 13(19), pages 1-25, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10885-:d:647223
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