IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i2d10.1007_s13198-022-01794-z.html
   My bibliography  Save this article

Multi-objective multi-item four dimensional green transportation problem in interval-valued intuitionistic fuzzy environment

Author

Listed:
  • Shivani

    (Department of Mathematics, Dr. B. R. Ambedkar National Institute of Technology)

  • Deepika Rani

    (Department of Mathematics, Dr. B. R. Ambedkar National Institute of Technology)

Abstract

This paper investigates the multi-objective multi-item four dimensional green transportation problem in an interval-valued intuitionistic fuzzy environment. Carbon emission is a critical problem in recent years and transportation activity is one of the main sources of carbon emission. In the transportation system, the rate of carbon emission depends on several factors such as type of fuel used, type of vehicles, load of the vehicles, driving style, traffic on the road, etc. In this study, we have described the impact of driving style on the carbon emission as well as on the transportation costs. The model has been proposed for the comparison of the amount of carbon emitted under two different driving styles, i.e., right(defensive) and wrong(aggressive). Also, the parameters of real-life multi-objective transportation problems are inherently unpredictable due to variety of factors. To handle the impreciseness and vagueness, interval-valued triangular intuitionistic fuzzy numbers (IVTIFNs) are used in the proposed model. Further, the proposed problem with IVTIFNs has been converted into a crisp form by using the expected value operator. Then the three programming techniques: weighted Tchebycheff metrics programming, interval-valued intuitionistic fuzzy programming and fuzzy TOPSIS method are employed to obtain the Pareto-optimal solution of the suggested model. A comparison is drawn between the Pareto-optimal solutions extracted with respect to two driving styles. The extracted results show that the right driving style provides a better solution in both environmental and economic aspects. Finally, a numerical application is given to demonstrate the applicability of the proposed study. Conclusions with the future research scope of this study are presented at last.

Suggested Citation

  • Shivani & Deepika Rani, 2024. "Multi-objective multi-item four dimensional green transportation problem in interval-valued intuitionistic fuzzy environment," 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. 15(2), pages 727-744, February.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:2:d:10.1007_s13198-022-01794-z
    DOI: 10.1007/s13198-022-01794-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-022-01794-z
    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/s13198-022-01794-z?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. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. K. B. Haley, 1962. "New Methods in Mathematical Programming---The Solid Transportation Problem," Operations Research, INFORMS, vol. 10(4), pages 448-463, August.
    3. Yu-Chung Tsao & Vu-Thuy Linh & Jye-Chyi Lu & Vincent Yu, 2018. "A supply chain network with product remanufacturing and carbon emission considerations: a two-phase design," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 693-705, March.
    4. Mojtaba Pirnazar & Hafez Hasheminasab & Arash Zand Karimi & Kaveh Ostad-Ali-Askari & Zahra Ghasemi & Majedeh Haeri-Hamedani & Elham Mohri-Esfahani & Saeid Eslamian, 2018. "The evaluation of the usage of the fuzzy algorithms in increasing the accuracy of the extracted land use maps," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 17(4), pages 307-321.
    5. Sumati Mahajan & S. K. Gupta, 2021. "On fully intuitionistic fuzzy multiobjective transportation problems using different membership functions," Annals of Operations Research, Springer, vol. 296(1), pages 211-241, January.
    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. Saptadeep Biswas & Prasad Belamkar & Deepshikha Sarma & Erfan Babaee Tirkolaee & Uttam Kumar Bera, 2025. "A multi-objective optimization approach for resource allocation and transportation planning in institutional quarantine centres," Annals of Operations Research, Springer, vol. 346(2), pages 781-825, March.
    2. Palash Sahoo, 2024. "Solution of a single-objective based three-stage 4DTP model with information crowdsourcing under disaster relief scenario: a hybrid random type-2 fuzzy approach," 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. 15(10), pages 4668-4713, 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. P. Senthil Kumar, 2019. "PSK Method for Solving Mixed and Type-4 Intuitionistic Fuzzy Solid Transportation Problems," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 10(2), pages 20-53, April.
    2. P. Senthil Kumar, 2024. "An efficient approach for solving type-2 intuitionistic fuzzy solid transportation problems with their equivalent crisp solid transportation problems," 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. 15(9), pages 4370-4403, September.
    3. P. Senthil Kumar, 2018. "A Simple and Efficient Algorithm for Solving Type-1 Intuitionistic Fuzzy Solid Transportation Problems," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 9(3), pages 90-122, July.
    4. Gourav Gupta & Shivani & Deepika Rani, 2024. "Neutrosophic goal programming approach for multi-objective fixed-charge transportation problem with neutrosophic parameters," OPSEARCH, Springer;Operational Research Society of India, vol. 61(3), pages 1274-1300, September.
    5. P.Senthil Kumar, 2018. "PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 7(4), pages 62-99, October.
    6. Sharmistha Halder (Jana) & Biswapati Jana, 2020. "Application of fuzzy programming techniques to solve solid transportation problem with additional constraints," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 30(1), pages 67-84.
    7. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    8. Collan, Mikael, 2008. "New Method for Real Option Valuation Using Fuzzy Numbers," Working Papers 466, IAMSR, Åbo Akademi.
    9. Wenyao Niu & Yuan Rong & Liying Yu & Lu Huang, 2022. "A Novel Hybrid Group Decision Making Approach Based on EDAS and Regret Theory under a Fermatean Cubic Fuzzy Environment," Mathematics, MDPI, vol. 10(17), pages 1-30, August.
    10. de Andres-Sanchez, Jorge, 2007. "Claim reserving with fuzzy regression and Taylor's geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 40(1), pages 145-163, January.
    11. Mikhailov, L., 2004. "A fuzzy approach to deriving priorities from interval pairwise comparison judgements," European Journal of Operational Research, Elsevier, vol. 159(3), pages 687-704, December.
    12. Hongyi Sun & Bingqian Zhang & Wenbin Ni, 2022. "A Hybrid Model Based on SEM and Fuzzy TOPSIS for Supplier Selection," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    13. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    14. Sakawa, Masatoshi & Kato, Kosuke, 1998. "An interactive fuzzy satisficing method for structured multiobjective linear fractional programs with fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 107(3), pages 575-589, June.
    15. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    16. Bogdana Stanojević & Milan Stanojević & Sorin Nădăban, 2021. "Reinstatement of the Extension Principle in Approaching Mathematical Programming with Fuzzy Numbers," Mathematics, MDPI, vol. 9(11), pages 1-16, June.
    17. Hector Diaz & Bruno Mazzorana & Bernhard Gems & Ivan Rojas & Nicole Santibañez & Pablo Iribarren & Mario Pino & Andrés Iroumé, 2022. "What do biphasic flow experiments reveal on the variability of exposure on alluvial fans and which implications for risk assessment result from this?," 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(3), pages 3099-3120, April.
    18. Svajone Bekesiene & Serhii Mashchenko, 2023. "On Nash Equilibria in a Finite Game for Fuzzy Sets of Strategies," Mathematics, MDPI, vol. 11(22), pages 1-12, November.
    19. Qian-Yun Tan & Cui-Ping Wei & Qi Liu & Xiang-Qian Feng, 2016. "The Hesitant Fuzzy Linguistic TOPSIS Method Based on Novel Information Measures," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(05), pages 1-22, October.
    20. Hsiao, Tzy-yih, 2006. "Establish standards of standard costing with the application of convergent gray zone test," European Journal of Operational Research, Elsevier, vol. 168(2), pages 593-611, January.

    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:ijsaem:v:15:y:2024:i:2:d:10.1007_s13198-022-01794-z. 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.