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PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems

PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems

P.Senthil Kumar
Copyright: © 2018 |Volume: 7 |Issue: 4 |Pages: 38
ISSN: 2156-177X|EISSN: 2156-1761|EISBN13: 9781522546283|DOI: 10.4018/IJFSA.2018100104
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MLA

Kumar, P.Senthil. "PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems." IJFSA vol.7, no.4 2018: pp.62-99. http://doi.org/10.4018/IJFSA.2018100104

APA

Kumar, P. (2018). PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems. International Journal of Fuzzy System Applications (IJFSA), 7(4), 62-99. http://doi.org/10.4018/IJFSA.2018100104

Chicago

Kumar, P.Senthil. "PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems," International Journal of Fuzzy System Applications (IJFSA) 7, no.4: 62-99. http://doi.org/10.4018/IJFSA.2018100104

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Abstract

This article proposes a method for solving intuitionistic fuzzy solid transportation problems (IFSTPs) in which only the transportation costs are represented in terms of intuitionistic fuzzy numbers (IFNs). The remaining parameters, namely: supply, demand and conveyance capacity, are all considered into crisp numbers. This type of STP is called a type-2 IFSTP. When solving the real life solid transportation problems (STPs) those tend to face the uncertainty state as well as hesitation due to many uncontrollable factors. To deal with uncertainty and hesitation many authors have suggested the intuitionistic fuzzy representation for the data. In this article, the author tried to categorise the STPs under the uncertain environment. He formulates the intuitionistic fuzzy STPs and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The PSK (P.Senthil Kumar) method for finding an intuitionistic fuzzy optimal solution for fully intuitionistic fuzzy transportation problem (FIFTP) is extended to solve the type-2 IFSTP and the optimal objective value of type-2 IFSTP is obtained in terms of TIFN. The main advantage of this method is that the optimal solution of type-2 IFSTP is obtained without using the basic feasible solution and the method of testing optimality. Moreover, the proposed method is computationally very simple and easy to understand. A case study is presented to illustrate the procedure of the proposed method.

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