Risk ranking in mega projects by fuzzy compromise approach: A comparative analysis

Abstract

This paper investigates the importance of risk ranking in mega projects by fuzzy compromise programming methods. To handle the limited resources problem to manage all risks, organizations can assess and prioritize important risks of mega projects. Three well-known decision-making methods, namely TOPSIS, VIKOR, and LINMAP, are employed in a fuzzy environment. One important issue considered in selecting the most appropriate fuzzy decision-making methods is the problem domain and method characteristics. Failing to address these characteristics may result in inappropriate outcomes or decisions. These methods are applied and compared for solving a risk ranking problem in a domain of mega projects. For the comprehensive study, six new aspects are introduced, including accuracy of methods, computational simplicity, large-scale problems, sensitivity to the parameters, discriminative measure, and inconsistency. Furthermore, a new fuzzy VIKOR method is extended in three different ways resulting in three different approaches to help project managers in handling mega project risks. Finally, the proposed fuzzy compromise approach is demonstrated with a real case study in the power industry.

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