Abstract
Accurate and computationally efficient methodologies for calculating the credibility of a fuzzy event not only constitute great challenges to researchers, but their importance to practitioners is steadily increasing ever since. In this regard, in this article, we develop two fuzzy simulation-based algorithms using respectively the uniform discretization method and the bisection approach. Facilitating the monotonicity property of shape functions of regular fuzzy numbers, we demonstrate the stability and reliability of our treatment using relevant theorems. Subsequently, a comparison analysis is conducted, which verifies higher levels of accuracy and efficiency for them when the standard stochastic discretization algorithm is used as a benchmark. Furthermore, these novel simulation-based algorithms are extended to consider the case of credibility of joint fuzzy events. A series of numerical experiments are developed for demonstrating clearly the accuracy and computational efficiency of the treatment.
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