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Fuzzy Transportation Problem by Using Triangular, Pentagonal and Heptagonal Fuzzy Numbers With Lagrange's Polynomial to Approximate Fuzzy Cost for Nonagon and Hendecagon

Author

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  • Ashok Sahebrao Mhaske

    (Dada Patil Mahavidyalaya, Karjat, India)

  • Kirankumar Laxmanrao Bondar

    (NES Science College, Nanded, India)

Abstract

The transportation problem is a main branch of operational research and its main objective is to transport a single uniform good which are initially stored at several origins to different destinations in such a way that the total transportation cost is minimum. In real life applications, available supply and forecast demand, are often fuzzy because some information is incomplete or unavailable. In this article, the authors have converted the crisp transportation problem into the fuzzy transportation problem by using various types of fuzzy numbers such as triangular, pentagonal, and heptagonal fuzzy numbers. This article compares the minimum fuzzy transportation cost obtained from the different method and in the last section, the authors introduce the Lagrange's polynomial to determine the approximate fuzzy transportation cost for the nanogon (n = 9) and hendecagon (n = 11) fuzzy numbers.

Suggested Citation

  • Ashok Sahebrao Mhaske & Kirankumar Laxmanrao Bondar, 2020. "Fuzzy Transportation Problem by Using Triangular, Pentagonal and Heptagonal Fuzzy Numbers With Lagrange's Polynomial to Approximate Fuzzy Cost for Nonagon and Hendecagon," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 9(1), pages 112-129, January.
    • Handle: RePEc:igg:jfsa00:v:9:y:2020:i:1:p:112-129
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    1. Nandi, Sandip & Granata, Giuseppe & Jana, Subrata & Ghorui, Neha & Mondal, Sankar Prasad & Bhaumik, Moumita, 2023. "Evaluation of the treatment options for COVID-19 patients using generalized hesitant fuzzy- multi criteria decision making techniques," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).

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