Optimal solution of neutrosophic linear fractional programming problems with mixed constraints

Das, Sapan Kumar; Edalatpanah, S. A.

doi:10.1007/s00500-022-07171-z

Cited by 5 publications

(1 citation statement)

References 26 publications

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“…Das and Chakraborty [34] considered a pentagonal NLP problem to solve it. Das and Dash [35] solved NLP problems with mixed constraints. Edalatpanah [36] presented a direct algorithm to solve the linear programming problems.…”

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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Section: Introductionmentioning

confidence: 99%

Fully Bipolar Single-Valued Neutrosophic Transportation Problems

Ahmed

Bashir

2022

Mathematical Problems in Engineering

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Balanced Neutrosophic Fermatean Graphs with Applications

Broumi,

Sivasankar,

Bakali

et al. 2024

Infosys Science Foundation Series

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Neutrosophic linear fractional optimization problem using fuzzy goal programming approach

Verma,

Singh

2024

Int. J. Model. Simul. Sci. Comput.

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This research paper develops an algorithm to solve a neutrosophic linear fractional optimization problem, where the cost of the objective functions, the technology coefficients, and the resources are neutrosophic numbers (triangular and trapezoidal numbers). Two defuzzification methods are used here to convert the neutrosophic linear fractional optimization problem into a multi-objective linear fractional optimization problem (MOLFOP). The fractional objective function is defuzzified using the component-wise optimization method, and the linear constraints are defuzzified using the aggregation ranking function strategy. Hence, the MOLFOP is then solved using the fuzzy goal programming method. In order to further explain our suggested algorithm, two numerical examples are solved at the end, and the outcomes obtained by our method are compared with the outcomes obtained using the other algorithm.

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Optimal solution of neutrosophic linear fractional programming problems with mixed constraints

Cited by 5 publications

References 26 publications

Fully Bipolar Single-Valued Neutrosophic Transportation Problems

Fully Bipolar Single-Valued Neutrosophic Transportation Problems

Balanced Neutrosophic Fermatean Graphs with Applications

Neutrosophic linear fractional optimization problem using fuzzy goal programming approach

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