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A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran

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  • Amir Khakbaz
  • Ali Nookabadi
  • S. Shetab-bushehri

Abstract

Traffic congestion is one of the main problems in large cities for which several approaches have been proposed. Park-and-ride is one of the best approaches that can remove traffic from the traffic network. Park-and-ride facilities are an important part of urban mass transit systems, effectively extending the service area and attracting commuters and other people who may not otherwise have used mass transit. However, its efficiency depends on its location in the urban network. In this research, we focus on travel time of shortest paths instead of the distance criterion for computing network traffic and develop a model for finding the best location(s) for siting park-and-ride systems so as to minimize the network traffic. The model is formulated based on population points, potential sites for park-and-ride establishment, and several Central Business District (CBDs). Then we present a Genetic algorithm that has been proved to be efficient in solving large size problems. Finally, the proposed model is used to locate park-and-ride facilities in the city of Isfahan, Iran. Copyright Springer Science+Business Media, LLC 2013

Suggested Citation

  • Amir Khakbaz & Ali Nookabadi & S. Shetab-bushehri, 2013. "A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran," Networks and Spatial Economics, Springer, vol. 13(1), pages 43-66, March.
    • Handle: RePEc:kap:netspa:v:13:y:2013:i:1:p:43-66
    DOI: 10.1007/s11067-012-9172-4
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    1. Elżbieta Macioszek & Agata Kurek, 2021. "The Analysis of the Factors Determining the Choice of Park and Ride Facility Using a Multinomial Logit Model," Energies, MDPI, vol. 14(1), pages 1-33, January.
    2. Wu, Shanhua & Yang, Zhongzhen, 2018. "Locating manufacturing industries by flow-capturing location model – Case of Chinese steel industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 1-11.
    3. Zhibin Chen & Stephen Spana & Yafeng Yin & Yuchuan Du, 2019. "An Advanced Parking Navigation System for Downtown Parking," Networks and Spatial Economics, Springer, vol. 19(3), pages 953-968, September.
    4. L. Zhang & Y. P. Wang & J. Sun & B. Yu, 2019. "The sightseeing bus schedule optimization under Park and Ride System in tourist attractions," Annals of Operations Research, Springer, vol. 273(1), pages 587-605, February.
    5. Puntipa Punyim & Ampol Karoonsoontawong & Avinash Unnikrishnan & Chi Xie, 2018. "Tabu Search Heuristic for Joint Location-Inventory Problem with Stochastic Inventory Capacity and Practicality Constraints," Networks and Spatial Economics, Springer, vol. 18(1), pages 51-84, March.
    6. Elżbieta Macioszek & Agata Kurek, 2020. "The Use of a Park and Ride System—A Case Study Based on the City of Cracow (Poland)," Energies, MDPI, vol. 13(13), pages 1-26, July.

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