A critical path problem using intuitionistic trapezoidal fuzzy number

Jayagowri, P.; Geetharamani, G.

doi:10.12988/ams.2014.43149

Cited by 8 publications

(11 citation statements)

References 6 publications

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“…As per the proposed algorithm, the calculations have been carried out based on Generalized Type-2 Trapezoidal Fuzzy Numbers using the proposed ranking function (5). The results of the calculations are presented in the following tables.…”

Section: A Case 1: Solution Of Critical Path Problem Based On Generamentioning

confidence: 99%

“…The results of the calculations are presented in the following tables. (19,20,21,30,39,47,48,49), (16,17,18,30,39,50,51,53), (13,14,15,30,39,54,55,56), (10,11,12,30,39,57,58,60), (7,8,9,30,39,61,62,63), (4,5,6,30,39,64,65 26, 27,29,36,37,38,39), (22,23,24,29,36,40,41,43), (19,20,21,29,36,…”

Section: Case 3: Solution Of Critical Path Problem Based On Generamentioning

confidence: 99%

“…In 2013, Ravi Shankar [10] developed a new fuzzy critical path method by applying a proposed approach of ranking of fuzzy numbers using centroid of centroids of fuzzy number to its distance from original point and Elizabeth and Sujatha [3] proposed a new ranking method based on acceptability and decision maker risk index to identify the fuzzy critical path in which they presented the fuzzy critical length in the nature of fuzzy membership function in the same year. In 2014, Jayagowri [5] made a novel approach to find the critical path based on intuitionistic trapezoidal fuzzy number in a directed acyclic graph. Subsequently, Oladeinde [8] carried out fuzzy critical path analysis of a project network based on metric distance ranking technique for ordering fuzzy numbers during the forward and backward pass computations to obtain the earliest start, earliest finish, latest start and latest finish time of the project's activities.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On Fuzzy Critical Path Method Based On Ranking Of Various Type-2 Fuzzy Quantities Using Centroid Of Centroids

2019

ijeat

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This paper proposes a simple approach to critical path analysis in a project network with activity times being intervals and which are converted into various Type-2 fuzzy quantities. The idea is based on generalized type-2 trapezoidal, hexagonal and octagonal fuzzy numbers and its ranking. The explicit form of membership functions of the type-2 fuzzy activity times is not required in the proposed approach. Moreover, the method is very simple and the numerical example is given for demonstrating and comparing the proposed approach with generalized type-2 trapezoidal, hexagonal and octagonal fuzzy numbers through proposed ranking function.

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Section: A Case 1: Solution Of Critical Path Problem Based On Generamentioning

confidence: 99%

Section: Case 3: Solution Of Critical Path Problem Based On Generamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On Fuzzy Critical Path Method Based On Ranking Of Various Type-2 Fuzzy Quantities Using Centroid Of Centroids

2019

ijeat

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“…Definition 11 (graded mean integration representation for trapezoidal (Atanassov) intuitionistic fuzzy number [16]). The membership and nonmembership functions of trapezoidal (Atanassov) intuitionistic fuzzy numbers are defined by Definition 3 as follows:…”

Section: Intuitionistic Fuzzy Numbers Then ≥ If and Only If Er( ) ≤ mentioning

confidence: 99%

Using Metric Distance Ranking Method to Find Intuitionistic Fuzzy Critical Path

Jayagowri¹,

Geetharamani

2015

Journal of Applied Mathematics

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Network analysis is a technique which determines the various sequences of activities concerning a project and the project completion time. The popular methods of this technique which is widely used are the critical path method and program evaluation and review techniques. The aim of this paper is to present an analytical method for measuring the criticality in an (Atanassov) intuitionistic fuzzy project network. Vague parameters in the project network are represented by (Atanassov) intuitionistic trapezoidal fuzzy numbers. A metric distance ranking method for (Atanassov) intuitionistic fuzzy numbers to a critical path method is proposed. (Atanassov) Intuitionistic fuzzy critical length of the project network is found without converting the (Atanassov) intuitionistic fuzzy activity times to classical numbers. The fuzzified conversion of the problem has been discussed with the numerical example. We also apply four different ranking procedures and we compare it with metric distance ranking method. Comparison reveals that the proposed ranking method is better than other raking procedures.

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“…In recent years, research on fuzzy numbers has attracted attention from scholars and experts, and has been widely used in the field of multi-attribute decision-making problems [1][2][3][4][5][6][7][8][9][10][11][12][13]. For example, Didier Dubois et al [2] provided a justification of symmetric triangular fuzzy numbers in the spirit of such inequalities.…”

Section: Introductionmentioning

confidence: 99%

A Multiple Attribute Decision-Making Method Based on Exponential Fuzzy Numbers

Sha

Fan

2016

MCA

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Regarding the multi-attribute decision-making problem where both the attribute value and attribute weight of a scheme are exponential fuzzy numbers, this paper proposes a fuzzy multiple attribute decision-making method based on exponential fuzzy numbers. The expected value and variance of the exponential fuzzy number were calculated according to the definitions of expectation and variance in probability theory. By comprehensively considering factors such as expected value, variance, and attitude preference of the decision-maker, this paper gave the score function of the exponential fuzzy number, based on which the accurate attribute weight can be determined. Subsequently, based on the distance measure between exponential fuzzy numbers, the distance was calculated between each scheme and the positive/negative ideal scheme, respectively, and the relative closeness of each scheme was solved; based on this, sorting and prioritizing were conducted. Finally, the feasibility and effectiveness of the proposed method were verified through case analysis.

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A critical path problem using intuitionistic trapezoidal fuzzy number

Cited by 8 publications

References 6 publications

On Fuzzy Critical Path Method Based On Ranking Of Various Type-2 Fuzzy Quantities Using Centroid Of Centroids

On Fuzzy Critical Path Method Based On Ranking Of Various Type-2 Fuzzy Quantities Using Centroid Of Centroids

Using Metric Distance Ranking Method to Find Intuitionistic Fuzzy Critical Path

A Multiple Attribute Decision-Making Method Based on Exponential Fuzzy Numbers

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