Abstract
Determining contingency reserve is critical to project risk management. Classic methods of determining contingency reserve significantly rely on historical data and fail to effectively incorporate certain types of uncertainties such as vagueness, ambiguity, and subjectivity. In this paper, an interval type-2 fuzzy risk analysis model (IT2FRAM) is introduced in order to determine the contingency reserve. In IT2FRAM, the membership functions for the linguistic terms used to describe the probability, impact of risk and the opportunity events are developed, optimized, and aggregated using interval type-2 fuzzy sets and the principle of justifiable granularity. IT2FRAM is an extension of a fuzzy arithmetic-based risk analysis method which considers such uncertainties and addresses the limitations of probabilistic and deterministic techniques of contingency determination methods. The contribution of IT2FRAM is that it considers the opinions of several subject matter experts to develop the membership functions of linguistic terms. Moreover, the effect of outlier opinions in developing the membership functions of linguistic terms are reduced. IT2FRAM also enables the aggregation of non-linear membership functions into trapezoidal membership functions. A hypothetical case study is presented in order to illustrate the application of IT2FRAM in Fuzzy Risk Analyzer© (FRA©), a risk analysis software.
Highlights
Dealing with uncertainties is an unavoidable challenge of every project
The objective of this paper is to propose an interval type-2 fuzzy risk analysis model (IT2FRAM) that extends fuzzy arithmetic-based risk analysis method (FRAM) [1] for determining contingency reserve
Type-2 fuzzy set concepts, and the principle of justifiable granularity are applied in IT2FRAM
Summary
Dealing with uncertainties is an unavoidable challenge of every project. The effect of uncertainties on project objectives, which may be positive or negative, can be controlled by implementing a risk management process. Various optimization methods are employed to adjust fuzzy sets including the simulated annealing algorithm [22], genetic algorithm [23,24], and tabu search [25] To address these gaps, the objective of this paper is to propose an interval type-2 fuzzy risk analysis model (IT2FRAM) that extends FRAM [1] for determining contingency reserve. The principle of justifiable granularity [11] is employed for determining the optimized interval type-2 membership functions of risk analysis concepts (i.e., linguistic variables including probability and impact) This principle provides an alternative to clustering methods in constructing information granules based on the criteria of coverage and specificity of data [32]. The use of IT2FRAM to determine the contingency reserve of projects is described This model is developed to determine the optimized membership values of linguistic terms of probability and impact for risk and opportunity events. The contributions and results of this research are presented, and potential future extensions are discussed
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