Abstract
A short note on methods of ranking fuzzy numbers in risk analysis problems
Highlights
Project management has become a key business process on strategic as well as operational level
We review briefly the methods for ranking fuzzy number in risk analysis
Numerous studies have indicated that fuzzy tools are becoming very popular in risk analysis problems because of the flexibility and efficiency they give to a decision maker (e.g. Chen and Chen, 2008; Akyar et al, 2013; Madhuri et al, 2014 and Alidoosti et al, 2012)
Summary
Project management has become a key business process on strategic as well as operational level. Most projects have restrictions in time, cost, scope and quality, there is a high level of uncertainty in any project too (Perminova et al, 2008). According to PMBOK, project risk is: “an uncertain event or condition that has a potential effect on at least one project objective” (Perminova et al, 2008). Fuzzy sets support linguistic vagueness effectively and provide approximate but very useful descriptions for ill-defined problems (Motawa et al, 2006). Numerous studies have indicated that fuzzy tools are becoming very popular in risk analysis problems because of the flexibility and efficiency they give to a decision maker Fuzzy numbers are defined by possibility distribution and can overlap each other.
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