A Novel Ranking Approach to Solving Fully LR-Intuitionistic Fuzzy Transportation Problems

Abhishekh,; Nishad, Anil Kumar

doi:10.1142/s1793005719500066

Cited by 11 publications

(6 citation statements)

References 24 publications

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“…After the invention of intuitionistic fuzzy set theory many authors (for instance, Kumar 2012a, b, c, 2013;Kumar and Hussain 2014a;Singh and Yadav 2015;Hussain 2015, 2016a;Ebrahimnejad and Verdegay 2016;Gupta and Anupum 2017;Kumar 2018b, c, d;Mahmoodirad et al 2018;Bharati and Singh 2018a;Ebrahimnejad and Verdegay 2018b;Hunwisai et al 2018;Pathade and Ghadle 2018;Abhishekh and Nishad 2018;Sidhu and Kumar 2019;Pratihar et al 2020;Smarandache and Broumi 2020) have solved transportation/linear programming problems under neutrosophic/IFE successfully. Similarly, a lot of works based on AP in IFE has been done by several researchers such as Mukherjee and Basu (2012), Hussain (2014b, c, d, 2016b, c), Kumar (2017b), Pothiraj and Rajaram (2017), Kumar (2018e, 2020a and many others.…”

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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“…Kumar and Hussain [33] used a computational approach to tackle fully intuitionistic fuzzy real life TPs. Abhishekh and Nishad [34] solved LR-intuitionistic FTPs by using ranking approach. Kaur et al [35] proposed different schemes to solve fully FTPs by using TrFNs.…”

Section: Introductionmentioning

confidence: 99%

Extended Transportation Models Based on Picture Fuzzy Sets

Mehmood

Bashir

2022

Mathematical Problems in Engineering

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Picture fuzzy set (PFS) is an extension of intuitionistic fuzzy set, and it is capable to analyze the transportation problems that contain uncertain and vague information. PFSs are applicable in situations where human decisions demand more variety of responses: yes, abstain, no, and rejection which cannot be addressed in the traditional FSs and IFSs. In this paper, we propose a technique to solve fully picture fuzzy transportation problems (FPFTPs) which are based on picture fuzzy linear programming formulation. Fully picture fuzzy transportation problems are developed by considering all the variables and parameters as nonnegative trapezoidal picture fuzzy numbers. A ranking function is used to transform picture fuzzy numbers into crisp numbers. A model is presented to explain the suggested scheme. Finally, comparison analysis of fully picture fuzzy transportation model with fully intuitionistic fuzzy transportation model and fully fuzzy transportation model is presented with pictorial illustrations.

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“…Singh and Yadav [4,5] suggested two different techniques to solve an intuitionistic fuzzy transportation problem (IFTPs) by using triangular intuitionistic fuzzy numbers (TIFNs). Abhishekh and Nishad [24] suggested a novel ranking function for finding an optimal solution to fully LR-intuitionistic fuzzy transportation problem. In an intuitionistic fuzzy environment, Edalatpanah [25] designed a model of data envelopment analysis with triangular intuitionistic fuzzy numbers (TIFNs) and established a strategy to solve it.…”

Section: Introductionmentioning

confidence: 99%

Fully Bipolar Single-Valued Neutrosophic Transportation Problems

Ahmed

Bashir

2022

Mathematical Problems in Engineering

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Transportation problem (TP) has its uses in real life because it has versatile applications. Real-life problems are often uncertain due to which it is difficult to find the accurate cost. The fuzzy set and intuitionistic fuzzy set are useful for handling the uncertainty, but these also have some limitations. For that reason, in this study, we worked on another set of values called bipolar single-valued neutrosophic set (BSNS) which is the generalization of crisp sets, fuzzy sets, and intuitionistic fuzzy sets to handle the uncertain, unpredictable, and insufficient information in real-life problems. In this study, we develop a new technique for solving transportation problems based on bipolar single-valued neutrosophic sets having nonnegative triangular bipolar single-valued neutrosophic numbers (TBSNNs). A score function is used to transform bipolar single-valued neutrosophic numbers (BSNNs) into crisp numbers. We compare our proposed model with fuzzy transportation and intuitionistic fuzzy transportation models and proved that bipolar single-valued neutrosophic transportation model is more admirable than the existing models. Furthermore, we apply the proposed technique to fully solve the bipolar single-valued neutrosophic transportation (FBSNT) model.

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A Novel Ranking Approach to Solving Fully LR-Intuitionistic Fuzzy Transportation Problems

Cited by 11 publications

References 24 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

Extended Transportation Models Based on Picture Fuzzy Sets

Fully Bipolar Single-Valued Neutrosophic Transportation Problems

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