Fuzzy TOPSIS Approach to Improve Quantitative Risk Analysis Considering Different Criteria and Their Mutual Effects

In PMBOK, a widely used project management standard, different risks are ranked based on two criteria: their probability and their impact on the project objectives. The multiplication of these two criteria is considered as the index of ranking the risks. This index ignores other criteria and also works weak in some special situations. In addition, it seems ambiguous when an expert is asked to determine the impact of risks on the project objectives via only one variable. This paper proposes a fuzzy multi-criteria approach to effectively analyze the impact of the risks on different important aspects of a project. The proposed approach works in a fuzzy environment with linguistic variables. The concept of linguistic variable is very useful in situations where decision problems are too complex or too ill-defined to be described properly using conventional quantitative expressions. Finally, the proposed approach is performed in a case study and the results have been compared with a deterministic TOPSIS method; which shows a significant difference in rankings when the fuzziness has been incorporated in the risk analysis process.