IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v309y2022i1d10.1007_s10479-021-04244-4.html
   My bibliography  Save this article

A genetic algorithm for solving bus terminal location problem using data envelopment analysis with multi-objective programming

Author

Listed:
  • Atefeh Taghavi

    (Ferdowsi University of Mashhad)

  • Reza Ghanbari

    (Ferdowsi University of Mashhad)

  • Khatere Ghorbani-Moghadam

    (Ferdowsi University of Mashhad)

  • Alireza Davoodi

    (Islamic Azad University)

  • Ali Emrouznejad

    (Aston University)

Abstract

Due to the urban expansion and population increasing, bus network design is an important problem in the public transportation. Functional aspect of bus networks such as the fuel consumption and depreciation of buses and also spatial aspects of bus networks such as station and terminal locations or access rate to the buses are not proper conditions in most cities. Therefore, having an efficient method to evaluate the performance of bus lines by considering both functional and spatial aspects is essential. In this paper, we propose a new model for the bus terminal location problem using data envelopment analysis with multi-objective programming approach. In this model, we want to find efficient allocation patterns for assigning stations terminals, and also we investigate the optimal locations for deploying terminals. Hence, we use a genetic algorithm for solving our model. By using the simultaneous combination of data envelopment analysis and bus terminal location problem, two types of efficiencies are optimized: Spatial efficiency as measured by finding allocation patterns with the most serving amount and the terminals’ efficiency in serving demands as measured by the data envelopment analysis efficiency score for selected allocation patterns. This approach is useful when terminals’ efficiency is one of the important criteria in choosing the optimal terminals location for decision-makers.

Suggested Citation

  • Atefeh Taghavi & Reza Ghanbari & Khatere Ghorbani-Moghadam & Alireza Davoodi & Ali Emrouznejad, 2022. "A genetic algorithm for solving bus terminal location problem using data envelopment analysis with multi-objective programming," Annals of Operations Research, Springer, vol. 309(1), pages 259-276, February.
    • Handle: RePEc:spr:annopr:v:309:y:2022:i:1:d:10.1007_s10479-021-04244-4
    DOI: 10.1007/s10479-021-04244-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-021-04244-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-021-04244-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Holmgren, Johan, 2013. "The efficiency of public transport operations – An evaluation using stochastic frontier analysis," Research in Transportation Economics, Elsevier, vol. 39(1), pages 50-57.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Saman Babaie-Kafaki & Reza Ghanbari & Nezam Mahdavi-Amiri, 2012. "An Efficient And Practically Robust Hybrid Metaheuristic Algorithm For Solving Fuzzy Bus Terminal Location Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1-25.
    4. Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
    5. Akin, Darcin & Kara, Derya, 2020. "Multicriteria analysis of planned intercity bus terminals in the metropolitan city of Istanbul, Turkey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 465-489.
    6. 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.
    7. Viton, Philip A., 1997. "Technical efficiency in multi-mode bus transit: A production frontier analysis," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 23-39, February.
    8. Saeedi, Hamid & Behdani, Behzad & Wiegmans, Bart & Zuidwijk, Rob, 2019. "Assessing the technical efficiency of intermodal freight transport chains using a modified network DEA approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 66-86.
    9. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, June.
    Full references (including those not matched with items on IDEAS)

    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. Marchetti, Dalmo & Wanke, Peter F., 2019. "Efficiency in rail transport: Evaluation of the main drivers through meta-analysis with resampling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 83-100.
    2. Merkert, Rico & Mulley, Corinne & Hakim, Md Mahbubul, 2017. "Determinants of bus rapid transit (BRT) system revenue and effectiveness – A global benchmarking exercise," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 75-88.
    3. Seyed Rakhshan & Ali Kamyad & Sohrab Effati, 2015. "Ranking decision-making units by using combination of analytical hierarchical process method and Tchebycheff model in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 505-525, March.
    4. Samet Güner & Erman Coşkun, 2016. "Determining the best performing benchmarks for transit routes with a multi-objective model: the implementation and a critique of the two-model approach," Public Transport, Springer, vol. 8(2), pages 205-224, September.
    5. Martin Eling, 2006. "Performance measurement of hedge funds using data envelopment analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 442-471, December.
    6. Nolan, James, 2001. "Productivity and Efficiency Changes Among Mid-Sized Transit," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 40(1).
    7. Yang, Guo-liang & Fukuyama, Hirofumi & Chen, Kun, 2019. "Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach," Omega, Elsevier, vol. 84(C), pages 141-159.
    8. Vassilios Babalos & Michael Doumpos & Nikolaos Philippas & Constantin Zopounidis, 2015. "Towards a Holistic Approach for Mutual Fund Performance Appraisal," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 35-53, June.
    9. Adel Hatami-Marbini & Madjid Tavana & Kobra Gholami & Zahra Ghelej Beigi, 2015. "A Bounded Data Envelopment Analysis Model in a Fuzzy Environment with an Application to Safety in the Semiconductor Industry," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 679-701, February.
    10. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    11. Xiaodong Chen & Anda Guo & Jiahao Zhu & Fang Wang & Yanqiu He, 2022. "Accessing performance of transport sector considering risks of climate change and traffic accidents: joint bounded-adjusted measure and Luenberger decomposition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 115-138, March.
    12. Peter Nijkamp & Soushi Suzuki, 2009. "A Generalized Goals-achievement Model in Data Envelopment Analysis: an Application to Efficiency Improvement in Local Government Finance in Japan," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(3), pages 249-274.
    13. Geng, ZhiQiang & Dong, JunGen & Han, YongMing & Zhu, QunXiong, 2017. "Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes," Applied Energy, Elsevier, vol. 205(C), pages 465-476.
    14. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    15. Malte L. Peters & Stephan Zelewski, 2016. "Opportunities and risks of satisficing levels in efficiency analyses from the perspective of sustainable development [Chancen und Risiken von Satisfizierungsgrenzen in Effizienzanalysen aus Perspek," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 24(2), pages 195-199, November.
    16. Thanh Ngo & Kan Wai Hong Tsui, 2022. "Estimating the confidence intervals for DEA efficiency scores of Asia-Pacific airlines," Operational Research, Springer, vol. 22(4), pages 3411-3434, September.
    17. Yaliu Yang & Yuan Wang & Cui Wang & Yingyan Zhang & Cuixia Zhang, 2022. "Temporal and Spatial Evolution of the Science and Technology Innovative Efficiency of Regional Industrial Enterprises: A Data-Driven Perspective," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    18. Pillai N., Vijayamohanan, 2019. "Measuring Energy Efficiency: An Application of Data Envelopment Analysis to Power Sector in Kerala," MPRA Paper 101945, University Library of Munich, Germany.
    19. Dario Maradin & Bojana Olgić Draženović & Saša Čegar, 2023. "The Efficiency of Offshore Wind Energy Companies in the European Countries: A DEA Approach," Energies, MDPI, vol. 16(9), pages 1-16, April.
    20. Taleb, Mushtaq & Khalid, Ruzelan & Ramli, Razamin & Ghasemi, Mohammad Reza & Ignatius, Joshua, 2022. "An integrated bi-objective data envelopment analysis model for measuring returns to scale," European Journal of Operational Research, Elsevier, vol. 296(3), pages 967-979.

    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:spr:annopr:v:309:y:2022:i:1:d:10.1007_s10479-021-04244-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.