Pessimistic evaluation of risks using ranking of generalized fuzzy numbers

The most important factors contributing to the risk of failure for any type of organization or system are related to poor performance, time pressure, low quality and high cost. In this paper we suggest a method to assess the overall risk of an organization or a system considering the changes in terms of time, cost, performance, and quality. We propose a pessimistic risk assessment as we consider that it is more realistic than existing approaches that mainly use the weighted average to assess the overall risk or adopt the traditional way to solve fuzzy inference systems. We use fuzzy maximum to identify the maximum of the impact of all risk factors. We propose a new algorithm to find the maximum of generalized fuzzy numbers representing the risk factors; our algorithm differentiates all non-identical fuzzy numbers. Actually, as we exploit the concept of fuzzy linguistic hedges for risk analysis, we need to differentiate fuzzy numbers even if they are very close to each other.