Since its inception in 1965, the theory of fuzzy sets has advanced in a variety of ways and in
many disciplines. Applications of this theory can be found, for example, in artificial …

This paper presents a comprehensive review of Uncertainty-Based Multidisciplinary Design
Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace …

Since its inception, the theory of fuzzy sets has advanced in a variety of ways and in many
disciplines. Applications of fuzzy technology can be found in artificial intelligence, computer …

Real-life decisions are usually made in the state of uncertainty. How do we model
optimization problems in uncertain environments? How do we solve these models? The …

The main characteristics of the real-world decision-making problems facing humans today
are multidimensional and have multiple objectives including eco nomic, environmental …

Fuzzy set theory was first developed for solving the imprecise/vague problems in the field of
artificial intelligence, especially for imprecise reasoning and modelling linguistic terms. In …

In the previous chapter, we have discussed a variety of computationally efficient approaches
for solving crisp multiple objective decision making problems. However, the input data, such …

This paper first presents a brief survey of the existing works on comparing and ranking any
two interval numbers on the real line and then, on the basis of this, gives two approaches to …

Lotfi et al.[Solving a full fuzzy linear programming using lexicography method and fuzzy
approximate solution, Appl. Math. Modell. 33 (2009) 3151–3156] pointed out that there is no …

In this paper, a method is suggested to solve the nonlinear interval number programming
problem with uncertain coefficients both in nonlinear objective function and nonlinear …