Trisectional fuzzy trapezoidal approach to optimize interval data based transportation problem

Bisht, Dinesh C. S.; Srivastava, Pankaj Kumar

doi:10.1016/j.jksus.2018.04.013

Cited by 19 publications

(5 citation statements)

References 15 publications

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“…After the invention of fuzzy set theory, many authors (for example, Mohideen and Kumar 2010;Sharma et al 2015;Baykasoglu and Subulan 2017;Kumar 2016aKumar , b, 2017aKumar , 2018aSujatha et al 2018;Vidhya and Ganesan 2018;Habib 2018;Bharati 2018;Mishra et al 2018;Saini et al 2018;Ngastiti et al 2018;Maheswari and Ganesan 2018;Sam'an et al 2018;Bisht and Srivastava 2018;Ebrahimnejad and Verdegay 2018a) have solved TPs under fuzzy environment successfully. Similarly, several authors have solved fuzzy assignment problems (FAPs) successfully.…”

Section: Historical Aspectsmentioning

confidence: 99%

Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set

Kumar

2020

Int J Syst Assur Eng Manag

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This eoffprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com".

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Section: Historical Aspectsmentioning

confidence: 99%

Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set

Kumar

2020

Int J Syst Assur Eng Manag

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“…This study proposes a modified form of the ranking technique used by B i s h t and S r i v a s t a v a [20] and A k y a r, E., H. A k y a r, and S. D ü z c e [27]. This method is based on intersection point of angular bisector called incenter of a triangle, where the abscissas of vertices represent the elements of triangular fuzzy number.…”

Section: Proposed Triangular Incenter Ranking Techniquementioning

confidence: 99%

“…The Problems 1 and 2 under consideration are compared with solution obtained by trisectional fuzzy trapezoidal approach [20]. The computational cost in the proposed method is less as compared to trisectional approach not only in fuzzification and ranking but also in number of iterations involved to obtain optimal solution as depicted in Table 11 and Table 13.…”

Section: Comparative Studymentioning

confidence: 99%

“…In the algorithm proposed transportation problem obtained is balanced after ranking for both problems, which makes it computationally faster and easier. [20] Proposed approach Trisectional approach [20] Proposed approach Trisectional approach [20] Proposed approach [20] Proposed approach Trisectional approach [20] Proposed approach Trisectional approach [20] Proposed approach Trisectional approach [20] Proposed approach The transportation cost for this interval based transportation problem will be optimum if the warehouses H1 receives product from suppliers L3, H2 receives product from suppliers L1 and L3, H3 receives product from suppliers L1 and H3 receives product from suppliers L2 and L3 (Table 12).…”

Section: Comparative Studymentioning

confidence: 99%

“…This is further justified by solving two real life examples. Results are also compared with existing trisectional trapezoidal method [20].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dichotomized Incenter Fuzzy Triangular Ranking Approach to Optimize Interval Data Based Transportation Problem

Srivastava

Bisht

2018

Cybernetics and Information Technologies

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This research article discusses the problems having flexible demand, supply and cost in range referred as interval data based transportation problems and these cannot be solved directly using available methods. The uncertainty associated with these types of problems motivates authors to tackle it by converting interval to fuzzy numbers. This confront of conversion has been achieved by proposing a dichotomic fuzzification approach followed by a unique triangular incenter ranking approach to optimize interval data based transportation problems. A comparison with existing methods is made with the help of numerical illustrations. The algorithm proposed is found prompt in terms of the number of iteration involved and problem formation. This method is practical to handle the transportation problems not having a single valued data, but data in form of a range.

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Fuzzy Approximate Optimal Solution of the Fuzzy Transportation Problems (FTP) Under Interval Form Using Monte Carlo Approach

Dasril

Sam'an

2022

Recent Advances in Soft Computing and Data Mining

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Trisectional fuzzy trapezoidal approach to optimize interval data based transportation problem

Cited by 19 publications

References 15 publications

Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set

Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set

Dichotomized Incenter Fuzzy Triangular Ranking Approach to Optimize Interval Data Based Transportation Problem

Fuzzy Approximate Optimal Solution of the Fuzzy Transportation Problems (FTP) Under Interval Form Using Monte Carlo Approach

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