IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i17p6479-d907036.html
   My bibliography  Save this article

Performance Optimisation of Public Transport Networks Using AHP-Dependent Multi-Aspiration-Level Goal Programming

Author

Listed:
  • Gang Lin

    (School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia)

  • Honglei Xu

    (School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia)

  • Shaoli Wang

    (School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6845, Australia)

  • Conghua Lin

    (School of Architecture and Planning, Fujian University of Technology, Fuzhou 350118, China)

  • Chenyu Huang

    (School of Design and Built Environment, Curtin University, Perth, WA 6102, Australia)

Abstract

This study proposes an optimisation approach to improve multiple-criteria aspiration-level public transportation performance by combining public transport criteria matrix analytic hierarchy process (PTCM-AHP) models and multi-aspiration-level goal programming. The approach uses the PTCM-AHP to calculate the system weights. Based on the weight values, the approach combines the multi-aspiration goal-level selection process in three different ways. The proposed approach was used to optimise public transportation networks in Bayswater, Cockburn, and Stonnington, Australia, to demonstrate the public transportation network performance optimisation process. By controlling the criteria goal value interval, this new approach combines decision-making plans and strategies to optimise various scenarios. The optimisation outcomes can be applied to provide guidelines for improving the performance of public transportation networks.

Suggested Citation

  • Gang Lin & Honglei Xu & Shaoli Wang & Conghua Lin & Chenyu Huang, 2022. "Performance Optimisation of Public Transport Networks Using AHP-Dependent Multi-Aspiration-Level Goal Programming," Energies, MDPI, vol. 15(17), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6479-:d:907036
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/17/6479/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/17/6479/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chang, Ching-Ter, 2011. "Multi-choice goal programming with utility functions," European Journal of Operational Research, Elsevier, vol. 215(2), pages 439-445, December.
    2. Philipp Heyken Soares, 2021. "Zone-based public transport route optimisation in an urban network," Public Transport, Springer, vol. 13(1), pages 197-231, March.
    3. Sadeghi, Mehdi & Ameli, Ahmad, 2012. "An AHP decision making model for optimal allocation of energy subsidy among socio-economic subsectors in Iran," Energy Policy, Elsevier, vol. 45(C), pages 24-32.
    4. Hocine, Amin & Zhuang, Zheng-Yun & Kouaissah, Noureddine & Li, Der-Chiang, 2020. "Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions," European Journal of Operational Research, Elsevier, vol. 285(2), pages 642-654.
    5. Rachel C. W. Wong & Tony W. Y. Yuen & Kwok Wah Fung & Janny M. Y. Leung, 2008. "Optimizing Timetable Synchronization for Rail Mass Transit," Transportation Science, INFORMS, vol. 42(1), pages 57-69, February.
    6. Philipp Heyken Soares & Christine L. Mumford & Kwabena Amponsah & Yong Mao, 2019. "An adaptive scaled network for public transport route optimisation," Public Transport, Springer, vol. 11(2), pages 379-412, August.
    7. Nassereddine, M. & Eskandari, H., 2017. "An integrated MCDM approach to evaluate public transportation systems in Tehran," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 427-439.
    8. M Larbani & B Aouni, 2011. "A new approach for generating efficient solutions within the goal programming model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 175-182, January.
    9. Gang Lin & Shaoli Wang & Conghua Lin & Linshan Bu & Honglei Xu, 2021. "Evaluating Performance of Public Transport Networks by Using Public Transport Criteria Matrix Analytic Hierarchy Process Models—Case Study of Stonnington, Bayswater, and Cockburn Public Transport Netw," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    10. Hui-Ping Ho & Ching-Ter Chang & Cheng-Yuan Ku, 2013. "On the location selection problem using analytic hierarchy process and multi-choice goal programming," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(1), pages 94-108.
    11. Chang, Ching-Ter, 2007. "Multi-choice goal programming," Omega, Elsevier, vol. 35(4), pages 389-396, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rodrigo Rodrigues de Freitas & Joyce Azevedo Caetano & Cintia Machado de Oliveira & Felipe do Carmo Amorim & Marcio Antelio Neves da Silva, 2022. "Transport Sustainability Index: An Application Multicriteria Analysis," Energies, MDPI, vol. 15(20), pages 1-14, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hocine, Amin & Kouaissah, Noureddine & Lozza, Sergio Ortobelli & Aouam, Tarik, 2024. "Modelling De novo programming within Simon’s satisficing theory: Methods and application in designing an optimal offshore wind farm location system," European Journal of Operational Research, Elsevier, vol. 315(1), pages 289-306.
    2. Gezen, Mesliha & Karaaslan, Abdulkerim, 2022. "Energy planning based on Vision-2023 of Turkey with a goal programming under fuzzy multi-objectives," Energy, Elsevier, vol. 261(PA).
    3. Gang Lin & Honglei Xu & Shaoli Wang & Conghua Lin & Fan Zhang & Junxiang Zhu, 2024. "Navigating Uncertainty: A Framework for Optimising Public Transport Networks’ Performance," Sustainability, MDPI, vol. 16(3), pages 1-23, February.
    4. Giri, Binoy Krishna & Roy, Sankar Kumar, 2024. "Fuzzy-random robust flexible programming on sustainable closed-loop renewable energy supply chain," Applied Energy, Elsevier, vol. 363(C).
    5. Chang, Ching-Ter & Chung, Cheng-Kung & Sheu, Jiuh-Biing & Zhuang, Zheng-Yun & Chen, Huang-Mu, 2014. "The optimal dual-pricing policy of mall parking service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 223-243.
    6. Hocine, Amin & Zhuang, Zheng-Yun & Kouaissah, Noureddine & Li, Der-Chiang, 2020. "Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions," European Journal of Operational Research, Elsevier, vol. 285(2), pages 642-654.
    7. Zheng-Yun Zhuang & Chi-Kit Ho & Paul Juinn Bing Tan & Jia-Ming Ying & Jin-Hua Chen, 2020. "The Optimal Setting of A/B Exam Papers without Item Pools: A Hybrid Approach of IRT and BGP," Mathematics, MDPI, vol. 8(8), pages 1-29, August.
    8. Zheng, Xiao-Xue & Chang, Ching-Ter, 2021. "Topology design of remote patient monitoring system concerning qualitative and quantitative issues," Omega, Elsevier, vol. 98(C).
    9. Javier Durán-Micco & Pieter Vansteenwegen, 2022. "A survey on the transit network design and frequency setting problem," Public Transport, Springer, vol. 14(1), pages 155-190, March.
    10. Ali Salmasnia & Amin Yazdekhasti, 2017. "A bi-objective model to optimize periodic preventive maintenance strategy during warranty period by considering customer satisfaction," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(4), pages 770-781, December.
    11. Shalabh Singh & Sonia Singh, 2022. "Shipment in a multi-choice environment: a case study of shipping carriers in US," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1195-1219, December.
    12. Yu-Jwo Tao & Yi-Shyuan Lin & Hsuan-Shih Lee & Guo-Ya Gan & Chang-Shu Tu, 2022. "Using a Product Life Cycle Cost Model to Solve Supplier Selection Problems in a Sustainable, Resilient Supply Chain," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    13. Zhang, Zhiying & Liao, Huchang & Tang, Anbin, 2022. "Renewable energy portfolio optimization with public participation under uncertainty: A hybrid multi-attribute multi-objective decision-making method," Applied Energy, Elsevier, vol. 307(C).
    14. Wang, Dian & D’Ariano, Andrea & Zhao, Jun & Zhong, Qingwei & Peng, Qiyuan, 2022. "Integrated rolling stock deadhead routing and timetabling in urban rail transit lines," European Journal of Operational Research, Elsevier, vol. 298(2), pages 526-559.
    15. Omar J. Ibarra-Rojas & Fernando López-Irarragorri & Yasmin A. Rios-Solis, 2016. "Multiperiod Bus Timetabling," Transportation Science, INFORMS, vol. 50(3), pages 805-822, August.
    16. Ghazale Kordi & Parsa Hasanzadeh-Moghimi & Mohammad Mahdi Paydar & Ebrahim Asadi-Gangraj, 2023. "A multi-objective location-routing model for dental waste considering environmental factors," Annals of Operations Research, Springer, vol. 328(1), pages 755-792, September.
    17. Wu, Weitiao & Liu, Ronghui & Jin, Wenzhou & Ma, Changxi, 2019. "Stochastic bus schedule coordination considering demand assignment and rerouting of passengers," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 275-303.
    18. Xu-Hui Li & Lin Huang & Qiang Li & Hu-Chen Liu, 2020. "Passenger Satisfaction Evaluation of Public Transportation Using Pythagorean Fuzzy MULTIMOORA Method under Large Group Environment," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    19. Farshad Noravesh & Kristiaan Kerstens, 2022. "Some connections between higher moments portfolio optimization methods," Papers 2201.00205, arXiv.org.
    20. Ibarra-Rojas, Omar J. & Rios-Solis, Yasmin A., 2012. "Synchronization of bus timetabling," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 599-614.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6479-:d:907036. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.