Many ranking methods have been proposed so far. However, there is yet no method that can
always give a satisfactory solution to every situation; some are counterintuitive, not …

This paper proposes a method for solving linear programming problems where all the
coefficients are, in general, fuzzy numbers. We use a fuzzy ranking method to rank the fuzzy …

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 …

As a continuation of the first part related to the first and second class of ordering approaches
this paper deals with the fulfilment of reasonable properties in the third class of ordering …

We present some interesting properties related to the area compensation procedure to
compare fuzzy numbers. It has been proved that this method produces more than a fuzzy …

Fuzzy numbers, and more generally linguistic values, are approximate assessments, given
by experts and accepted by decision-makers when obtaining more accurate values is …

In this paper, we present a new method for fuzzy risk analysis based on ranking generalized
fuzzy numbers with different heights and different spreads. First, we present a new method …

Starting from a subjective assignation of weights related to the relative importance of the
different level sets, we define a new method of comparison of fuzzy numbers. This procedure …

Interval fuzzy preference relation is a useful tool to express decision maker's uncertain
preference information. How to derive the priority weights from an interval fuzzy preference …