Linear programming (LP) is the most widely used optimization technique for solving real-life problems because of its simplicity and efficiency. Although conventional LP models require precise data, managers and decision makers dealing with real-world optimization problems often do not have access to exact values. Fuzzy sets have been used in the fuzzy LP (FLP) problems to deal with the imprecis...

As the assessment of pavement performance has considerable repercussions for construction quality roads, study procedure used is extremely critical. Riding index (RQI), condition (PCI), structure strength (PSSI), skid resistance (SRI), and antirutting (ARI) are selected as indexes performance. Then, entropy weight-variable fuzzy sets model introduced. Second, a relative membership degree matrix...

This paper deals with boolean linear programming problems involving coefficients in the objective function as fuzzy numbers. In the study of these problems different approaches can be proposed to use ranking fuzzy numbers methods and fuzzy preference relations obtaining auxiliary classical boolean programming problems, and to use the representation theorem obtaining a convex set with extreme po...

Linear programming problems with fuzzy coefficients in the objective function are considered. Emphasis is on the dependence of the optimal solution from linear perturbations of the membership functions of the objective function coefficients as well as on the computation of a robust solution of the fuzzy linear problem if the membership functions are not surely known.

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...

In fuzzy set theory, it is well known that a triangular fuzzy number can be uniquely determined through its position and entropies. In the present communication, we extend this concept on triangular intuitionistic fuzzy number for its one-to-one correspondence with its position and entropies. Using the concept of fuzzy entropy the estimators of the intuitionistic fuzzy regression coefficients h...

Ranking fuzzy numbers plays an important role in data analysis, decision making optimization, forecasting etc. The last few decades have seen a large number of methods investigated for ranking fuzzy numbers. In this paper, a new approach is proposed for the ranking of generalized trapezoidal fuzzy numbers namely Haar ranking and is based on the approximate coefficients and detailed coefficients...

Fuzzy random variable is a measurable function from a probability space to the set of fuzzy variables, while random fuzzy variable is a function from a credibility space to the set of random variables. The concepts of independent and identically distributed fuzzy random variables and random fuzzy variables are presented, and some useful properties are discussed.