A developed distance method for ranking generalized fuzzy numbers

AbstractThe Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is considered among the most frequently used techniques to deal with multi-criteria group decision-making (MCGDM) conflicts. In this article, we have presented an extended TOPSIS technique in the framework of interval type-2 trapezoidal Pythagorean fuzzy numbers (IT2TrPFN). We first projected a novel approach to evaluate the distance between them using ordered weighted averaging operator and $$(\alpha ,\beta )$$ ( α , β ) -cut. Subsequently, we widen the concept of TOPSIS method formed on the distance method with IT2TrPFNs and applied it on MCGDM dilemma by considering the attitudes and perspectives of the decision-makers. Lastly, an application of solar tracking system and numerous contrasts with the other existing techniques are presented to express the practicality and feasibility of our projected approach.

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Availability Analysis of Industrial Systems Using Markov Process and Generalized Fuzzy Numbers

MAPAN ◽

10.1007/s12647-018-0290-4 ◽

2018 ◽

Vol 34 (1) ◽

pp. 79-91

Author(s):

Neha Singhal ◽

S. P. Sharma

Keyword(s):

Markov Process ◽

Fuzzy Numbers ◽

Industrial Systems ◽

Availability Analysis ◽

Generalized Fuzzy Numbers

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Inventory Model with Demand Dependant on Unit Cost- Input Parameters as Triangular Fuzzy Numbers

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i2.1911 ◽

2021 ◽

Vol 12 (2) ◽

Author(s):

R. Kasthuri, Et. al.

Keyword(s):

Fuzzy Numbers ◽

Unit Cost ◽

Inventory Model ◽

Average Total Cost ◽

Triangular Fuzzy Numbers ◽

Lot Size ◽

Distance Method ◽

Total Cost ◽

Signed Distance ◽

Fuzzy Environment

This paper considers an inventory model in which the shortages are backlogged and the demand is dependent on unit cost. An optimum value for average total cost is calculated by considering various input costs, lot size and maximum inventory under fuzzy environment. The process of defuzzification is done by using the signed distance method. Numerical example and sensitivity analysis is given for calculating both crisp and fuzzy values of the total cost.

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Ranking Fuzzy Numbers by Centroid Method

Malaysian Journal of Fundamental and Applied Sciences ◽

10.11113/mjfas.v8n3.134 ◽

2014 ◽

Vol 8 (3) ◽

Author(s):

Fateen Najwa Azman ◽

Lazim Abdullah

Keyword(s):

Numerical Calculation ◽

Decision Process ◽

Fuzzy Numbers ◽

New Method ◽

Centroid Method ◽

Generalized Fuzzy Numbers

Ranking fuzzy numbers are one of the important tools in decision process. There are many methods that have been proposed by a number of researchers but most of the methods are nondiscriminating and counterintuitive. Thus, proposing a new method for ranking fuzzy numbers are very prominent. The main objective of this paper is to get better ranking results to rank generalized fuzzy numbers than existing method. This paper reviews the centroid method in ranking fuzzy numbers by several researchers. A new calculation of centroid method will be proposed in this paper. At the end of the paper, a numerical calculation and a comparison of centroid method between the proposed method and other researchers’ method will be showed to check on its consistency.

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Fuzzification of EOQ Model Under the Condition of Permissible Delay in Payments

International Journal of Strategic Decision Sciences ◽

10.4018/jsds.2012040101 ◽

2012 ◽

Vol 3 (2) ◽

pp. 1-19 ◽

Cited By ~ 5

Author(s):

Chandra K. Jaggi ◽

Anuj Sharma ◽

Reena Jain

Keyword(s):

Fuzzy Numbers ◽

Delay Period ◽

Order Quantity ◽

Distance Method ◽

Permissible Delay In Payments ◽

Signed Distance ◽

Eoq Model ◽

Fuzzy Environment ◽

Delay In Payments ◽

The Cost

This paper formulates an economic order quantity inventory model under the condition of permissible delay in payments in fuzzy environment. All the parameters of the model, excluding permissible delay period and cycle length, are taken to be trapezoidal Fuzzy numbers. The arithmetic operations are defined under the function principle. The cost function has been defuzzified using signed distance method and thereby solved to obtain the optimal replenishment period. The numerical example is presented to show the validity of the model followed by sensitivity analysis.

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