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Sorting Out Fuzzy Transportation Problems via ECCT and Standard Deviation

Sorting Out Fuzzy Transportation Problems via ECCT and Standard Deviation

Krishna Prabha Sikkannan, Vimala Shanmugavel
Copyright: © 2021 |Volume: 12 |Issue: 2 |Pages: 14
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781799861218|DOI: 10.4018/IJORIS.20210401.oa1
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MLA

Sikkannan, Krishna Prabha, and Vimala Shanmugavel. "Sorting Out Fuzzy Transportation Problems via ECCT and Standard Deviation." IJORIS vol.12, no.2 2021: pp.1-14. http://doi.org/10.4018/IJORIS.20210401.oa1

APA

Sikkannan, K. P. & Shanmugavel, V. (2021). Sorting Out Fuzzy Transportation Problems via ECCT and Standard Deviation. International Journal of Operations Research and Information Systems (IJORIS), 12(2), 1-14. http://doi.org/10.4018/IJORIS.20210401.oa1

Chicago

Sikkannan, Krishna Prabha, and Vimala Shanmugavel. "Sorting Out Fuzzy Transportation Problems via ECCT and Standard Deviation," International Journal of Operations Research and Information Systems (IJORIS) 12, no.2: 1-14. http://doi.org/10.4018/IJORIS.20210401.oa1

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Abstract

A well-organized arithmetical procedure entitled standard deviation is employed to find the optimum solution in this paper. This technique has been divided into two parts. The first methodology deals with constructing the entire contingency cost table, and the second deals with optimum allocation. In this work, the method of magnitude is used for converting fuzzy numbers into crisp numbers as this method is better than the existing methods. This technique gives a better optimal solution than other methods. A numerical example for the new method is explained, and the authors compared their method with existing methods such as north west corner method, least cost method, and Vogel's approximation method.