Metric Distance Ranking Technique for Fuzzy Critical Path Analysis

Oladeinde, MH; Oladeinde, CA

doi:10.4314/jasem.v18i4.4

Cited by 3 publications

(4 citation statements)

References 4 publications

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“…Keeping these issues in mind, a study proposed that incorporating experts' opinions and the fuzzy Delphi method might be effective while using the PERT [15]. It is also suggested that uncertainty can be reduced by using experts' opinions to forecast the timeliness and cost estimations of activities in the form of fuzzy sets [72]. The scheduling results from the CPM and PERT were analyzed using a fuzzy method to improve scheduling in project management [28].…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Project Management Techniques for Timeline and Budgeting Estimates of Startups

Khan,

Ali,

Garai-Fodor

et al. 2023

Sustainability

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This study aims to develop a framework by incorporating well-proven project management techniques to help startup owners effectively set up ventures and secure early-stage financing. Startups not only open ways for innovative and updated technologies in the markets but also bring employment opportunities in a country that eventually increase productivity and the per capita income of a country. Despite all the benefits, the success rate of startups is meager, especially in developing countries, due to ineffective management and vague business plans. Therefore, this study aims to facilitate entrepreneurs using well-proven project management techniques from the literature and devise a new framework applied to a business case, as discussed in this paper. This study presents an approach to project management techniques for smartphone app-based startups. This study utilizes the fuzzy PERT (FPERT) for the best completion time and budget estimates. Experts’ opinions from eight private limited companies have been analyzed using FPERT. The critical path method (CPM) is also used to schedule activities. Finally, a techno-economic analysis is also performed to show the growth potential of such a startup, e-Karsaz. This study aims to help startups secure early-stage financing. Tech-based business ideas need to be commercialized in developing countries like Pakistan. There is a need to show long-term profitability to make an idea stand out among others and secure early-stage financing. The scope of project management techniques is confined to construction-based projects. The results show that it would take around 692 days for the e-Karsaz startup to become fully operational, with the capital budget estimated at around PKR 1.3 billion. The techno-economic analysis shows the project is economically viable with an internal rate of return (IRR) equal to 92 percent and a benefit-to-cost ratio (BCR) equal to 10. The sensitivity analysis, including five scenarios of weighted average cost of capital (WACC), shows that the project remains economically viable even if the required rate of return goes over 20 percent. This study is helpful for startups to make time and budget estimates and to show the growth potential to secure early-stage financing.

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Section: Literature Reviewmentioning

confidence: 99%

Application of Project Management Techniques for Timeline and Budgeting Estimates of Startups

Khan,

Ali,

Garai-Fodor

et al. 2023

Sustainability

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“…The above distance measure describe the idea that more closer two fuzzy numbers be, more nearer are the truths of one being greater than or equal to the other. Definition 12 [40] The metric distance ranking technique was proposed by Chen and Cheng (2005) to order fuzzy numbers. Let two fuzzy numbers A and B be defined as follows:…”

Section: Definition: 11[22]mentioning

confidence: 99%

A Comparative Study of TOPSIS Method via Different Distance Measure

Talukdar¹,

Dutta²

2019

IJRAT

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One of the techniques used to support strong decision making in domains where selection of best alternative is highly complex is the Fuzzy TOPSIS method. In TOPSIS procedure different distance measures are used to calculate the distance of each fuzzy number from both Fuzzy Positive Ideal Solution (FPIS) and Fuzzy negative Ideal Solution (FNIS). In this paper, six well known distance measures have been taken into account which are available in literature and applied to TOPSIS procedure to perform a comparative study throughout numerical problems. The main purpose is to compare the stability and reliability of TOPSIS method in decision science through different distance measures. Fuzzy triangular number is used in our entire case study.

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“…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%

“…48,50,61,62,64), (40,42,50,61,69,71), (37,39,50,61,72,75), (34,36,50,61,76,78), (31,33,50,61,79,82), (25,27,50,61,86,89))((0,0,0,37,45,55), (0,0,0,37,78,88), (0,0,0,37,93,106), (0,0,0,37,111,122), (0,0,0,37,127,139), (0,0,0,37,160,172)) C -D((25,27,29,36,37,39),(19,21,29,36,44,46),(16,18,29,36,47,50),(13,15,29,36,51,53),(10,12,29,36,54,57),(4,6,29,36,61,64)) ((0,0,0,28,39,51), (0,0,0,28,78,90), (0,0,0,28,96,111), (0,0,0,28,117,130), (0,0,0,28,136,150), (0,0,0,28,175,189)) B -E ((60,63,67,75,76,78), (54,56,67,75,83,86), (50,53,67,75,87,89), (47,49,67,75,91,93), (44,46,67,75,94,97), (38,40,67,75,101,104)) ((0,4,14,60,68,79), (0,0,14,60,102,112), (0,0,14,60,117,131), (0,0,14,60,136,147), (0,0,14,60,152,164), (0,0,14,60,185,197)) C -E ((66,68,70,78,79,81), (60,62,70,78,86,88), (57,59,70,78,89,92), (54,56,70,78,93,95), (51,53,70,78,96,99), (45,47,70,78,103,106)) ((2,12,22,67,75,85), (0,0,22,67,108,118), (0,0,22,67,123,136), (0,0,22,67,141,152), (0,0,22,67,157,169), (0,0,22,67,190,202)) D -E ((75,77,80,92,93,95), (69,71,80,92,100,102), (66,68,80,92,103,106), (63,65,80,92,107,110), (60,62,80,92,111,113), (54,56,80,92,118,120)) ((0,0,0,28,39,51), (0,0,0,28,78,90), (0,0,0,28,96,111), (0,0,0,28,117,130), (0,0,0,28,136,150), (0,0,0,28,175,189)) 22,95,293,319), (0,0,22,95,365,391)) ((0,0.03,0.06,0.24,0.29,0.35), (0,0,0.06,0.24,0.48,0.53), (0,0,0.06,0.24,0.56,0.63), (0,0,0.06,0.24,0.66,0.72), (0,0,0.06,0.24,0.75,0.82), (0,0,0.06,0.24,0.93,1)) A-C-D-E ((0,0,0,84,117,153), (0,0,0,84,234,270), (0,0,0,84,288,333), (0,0,0,84,351,390), (0,0,0,84,408,450), (0,0,0,84,525,567)) ((0,0,0,0.15,0.21,0.27), (0,0,0,0.15,0.41,0.48), (0,0,0,0.15,0.51,0.59), (0,0,0,0.15,0.62,0.69), (0,0,0,0.15,0.72,0.79), (0,0,0,0.15,0.93,1)) 0.268, R( ) = 0.245, R( ) = 0.198, R( ) =0.208 For = 0.5, R( ) = 0.273, R( ) = 0.261, R( ) = 0.238, R( ) =0.243 For = 0, R( ) = R( ) = R( ) = R( ) = 0.278 Here minimum ranks are 0.198, 0.238 and 0.278 for = 1, = 0.5 and = 0 respectively. So the critical path is A -C -D -E.…”

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confidence: 99%

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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Metric Distance Ranking Technique for Fuzzy Critical Path Analysis

Cited by 3 publications

References 4 publications

Application of Project Management Techniques for Timeline and Budgeting Estimates of Startups

Application of Project Management Techniques for Timeline and Budgeting Estimates of Startups

A Comparative Study of TOPSIS Method via Different Distance Measure

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

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