A Fuzzy Decision-Making Methodology for Risk Response Planning in Large-Scale Projects

Abstract

Risk response planning is one of the main phases in the project risk management and has major impacts on the success of a large-scale project. Since projects are unique, and risks are dynamic through the life of the projects, it is necessary to formulate responses of the

important risks. The conventional approaches tend to be less effective in dealing with the impreciseness of risk response planning. This paper presents a new decision-making methodology in a fuzzy environment to evaluate and select the appropriate responses for project

risks. To this end, two fuzzy well-known decision-making techniques, namely, decision tree and TOPSIS (technique for order preference by similarity to ideal solution), are extended based on multiple selected criteria, simplifying parameterized metric distance and fuzzy

similarity measure. Finally, a case study in an oil and gas project in Iran is provided to show the suitability of the proposed fuzzy methodology in large-scale practical situations.