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A new dynamic score function approach to optimize a special class of Pythagorean fuzzy transportation problem

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  • Priyanka Nagar

    (Jaypee Institute of Information Technology)

  • Pankaj Kumar Srivastava

    (Jaypee Institute of Information Technology)

  • Amit Srivastava

    (Jaypee Institute of Information Technology)

Abstract

Endangered species are very important for our biodiversity and relocation is necessary to protect these species from extinction. In this paper, a pythagorean species fuzzy transportation problem is adopted to relocate these species. A new score function is proposed to defuzzify the pythagorean fuzzy numbers. In the literature, there are score functions in which the information about hesitation is missing but the proposed score function has the information about hesitation. Therefore, one can attain the accurate information about the pythagorean fuzzy numbers. Using proposed approach, these species are transferred at very minimum cost. To check the validity of proposed score function, comparison have been made with other existing score functions. Numerical illustrations are given to justify the proposed approach. Finally, a comparative study for transportation cost and allocations with the existing methods has been done to show the effectiveness of proposed score function.

Suggested Citation

  • Priyanka Nagar & Pankaj Kumar Srivastava & Amit Srivastava, 2022. "A new dynamic score function approach to optimize a special class of Pythagorean fuzzy transportation problem," 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. 13(2), pages 904-913, June.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:2:d:10.1007_s13198-021-01339-w
    DOI: 10.1007/s13198-021-01339-w
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    References listed on IDEAS

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    1. José Alcantud & Annick Laruelle, 2014. "Dis&approval voting: a characterization," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(1), pages 1-10, June.
    2. Liu, Shiang-Tai & Kao, Chiang, 2004. "Solving fuzzy transportation problems based on extension principle," European Journal of Operational Research, Elsevier, vol. 153(3), pages 661-674, March.
    3. Sujeet Kumar Singh & Shiv Prasad Yadav, 2016. "A new approach for solving intuitionistic fuzzy transportation problem of type-2," Annals of Operations Research, Springer, vol. 243(1), pages 349-363, August.
    4. Laxminarayan Sahoo, 2019. "Solving matrix games with linguistic payoffs," 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. 10(4), pages 484-490, August.
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