This paper develops a solution method for Chance Constrained Programming problem, where the random variable in the right hand side of the chance constraints follows different fuzzy distributions. The methodology is verified through numerical examples.

In real projects, the trade-off between the project cost and the project completion time, and the environmental uncertainty are aspects of considerable importance for managers. For complex environment with more than one type of uncertainty, this paper presents three types of time–cost trade-off models, in which the project environment is described via introducing the fuzzy random theory. The ex...

A complex structure has many uncertain factors and how to make a more accurate analysis on the structure reliability by a method is the key in engineering calculation. Rough set theory is utilized to analyze the fuzzy, random and uncertain factors and upper and lower approximation set relation is used to calculate the value taking interval of reliability index to make reliability index analysis...

This paper studies a facility location model with fuzzy random parameters and its swarm intelligence approach. A Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRFLM) is built in which both the costs and demands are assumed to be fuzzy random variables, and the capacity of each facility is unfixed but a decision variable assuming continuous values. Under this setting, the V...

Due to the existing of various kinds of uncertainties, predicting structural performance is always a great challenge in practical applications. The reliability of structure under the probabilistic uncertainty has been well studied in the past decade. However, the randomness is not the only attribute of reality. This paper attempts to investigate approach for the structural reliability analysis ...

The mean and the variance value of a random variable play an important role in statistical analysis. Sometimes the available observations are not precise, and we want to test the hypotheses of mean and variance in such environment. Hence, in this paper, we first extend and introduced L2−metric based on imprecise (fuzzy) observations, and then, the concepts of fuzzy test statistics are defined b...

This paper considers two-level linear programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed in order to maximize both of possibility and probability with respect to the objective function value. After the original random fuzzy two-level programming problem is reduced to a deterministic one through ...

Abstract: In this paper a non-repairable multi-state system with imprecise probabilities and performance rates are taken, representing imprecise probabilities by interval valued probabilities. These intervals are evaluated by computing bound of interval valued ordinary differential equation of the system. For imprecise performance rates random fuzzy variables are introduced. The proposed method...

Two major approaches to deal with randomness or impression involved in mathematical programming problems have been developed. The one is called stochastic programming, and the other is called fuzzy programming. In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in constraints. Using the concept of simple recourse, such multiobjective st...

This paper incorporates fuzzy random variables with a portfolio selection problem based on the single index model. The rate of return on each investment can be represented with a fuzzy random variable. A novel decision-making model based both on possibilistic programming and on stochastic programming. It is shown that the formulated problem is transformed into the deterministic equivalent nonli...