Project scheduling method using triangular intuitionistic fuzzy numbers and triangular fuzzy numbers

Elizabeth, S.; Sujatha, L.

doi:10.12988/ams.2015.410852

Cited by 15 publications

(15 citation statements)

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“…In this paper, metric distance ranking method is introduced to identify the (Atanassov) intuitionistic fuzzy critical path. And also we used Rezvani [12] ranking method, Euclidian Distance measure [10] similarity ranking method [15], and graded Journal of Applied Mathematics mean integration ranking method to rank the path. Using Definitions 8 and 11 of ranking methods, we cannot suitably identify the required optimal path.…”

Section: Resultsmentioning

confidence: 99%

“…Definition 9 (Euclidean Ranking (ER) technique for trapezoidal (Atanassov) intuitionistic fuzzy numbers [10]). Let = {( , , , )( , , , )} be the th fuzzy path length and let max = {( , , , )( , , , )} = ( max , max ) be the fuzzy longest length then the Euclidean Ranking of is denoted by…”

Section: Definition 3 (Trapezoidal Intuitionistic Fuzzy Number) An (mentioning

confidence: 99%

“…The earliest starting (Atanassov) intuitionistic fuzzy times are as follows. Trail run (5, 7, 9, 15); (6,10,12,14) For membership function, …”

Section: Examplementioning

confidence: 99%

“…To find rank using Euclidean Distance method [10], we need max = (−38, 4, 42, 132) from membership function max = (−57, −16, 28, 88) from nonmembership function using Table 4. To find rank using similarity ranking [15], we need̃m in = (−132, −36, 26, 86) from membership and̃m ax = (−57, −16, 28, 88) from nonmembership function using Table 4.…”

Section: Different Ranking Approachmentioning

confidence: 99%

“…Elizabeth and Sujatha [9,10] introduced new ranking methods to find fuzzy critical path problem for project network.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Resultsmentioning

confidence: 99%

Section: Definition 3 (Trapezoidal Intuitionistic Fuzzy Number) An (mentioning

confidence: 99%

“…The earliest starting (Atanassov) intuitionistic fuzzy times are as follows. Trail run (5, 7, 9, 15); (6,10,12,14) For membership function, …”

Section: Examplementioning

confidence: 99%

Section: Different Ranking Approachmentioning

confidence: 99%

“…Elizabeth and Sujatha [9,10] introduced new ranking methods to find fuzzy critical path problem for project network.…”

Section: Introductionmentioning