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Estimation of Construction Activity Duration Under Uncertainty Using Discrete Fuzzy Weighted Average Algorithm

Estimation of Construction Activity Duration Under Uncertainty Using Discrete Fuzzy Weighted Average Algorithm

Pejman Rezakhani, Kasim A. Korkmaz
Copyright: © 2022 |Volume: 10 |Issue: 1 |Pages: 19
ISSN: 2643-8089|EISSN: 2643-8097|EISBN13: 9781683183600|DOI: 10.4018/IJPMPA.301598
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MLA

Rezakhani, Pejman, and Kasim A. Korkmaz. "Estimation of Construction Activity Duration Under Uncertainty Using Discrete Fuzzy Weighted Average Algorithm." IJPMPA vol.10, no.1 2022: pp.1-19. http://doi.org/10.4018/IJPMPA.301598

APA

Rezakhani, P. & Korkmaz, K. A. (2022). Estimation of Construction Activity Duration Under Uncertainty Using Discrete Fuzzy Weighted Average Algorithm. International Journal of Project Management and Productivity Assessment (IJPMPA), 10(1), 1-19. http://doi.org/10.4018/IJPMPA.301598

Chicago

Rezakhani, Pejman, and Kasim A. Korkmaz. "Estimation of Construction Activity Duration Under Uncertainty Using Discrete Fuzzy Weighted Average Algorithm," International Journal of Project Management and Productivity Assessment (IJPMPA) 10, no.1: 1-19. http://doi.org/10.4018/IJPMPA.301598

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Abstract

This paper presents a qualitative risk assessment tool based on fuzzy set theory to estimate the amount of activity duration overrun under the combinatory effect of multiple risk factors. Applying proposed methodology, a set of duration modifiers to calculate the optimistic, most-likely and pessimistic duration values under uncertainty are calculated. To elaborate the methodology, a simulated bridge project with ten risk factors affecting activities duration is presented. Proposed model contributes to knowledge that could help minimize the schedule overrun and improve risk mitigation strategies through providing risk-based duration estimates instead of discrete values. Advantages of the developed approach compared to existing models include (1) considering the combinatory effect of multiple risk factors on activity duration, (2) accounting for uncertainty in experts’ evaluations by employing the interval-valued fuzzy numbers, and (3) utilizing a discrete fuzzy weighted average algorithm which avoids creation of incorrect fuzzy membership functions.

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