M Inuiguchi, H Ichihashi, H Tanaka - Stochastic versus fuzzy approaches …, 1990 - Springer
In this paper, a survey of the major types of fuzzy programming is provided classifying into the following three categories; mathematical programming with vagueness, mathematical …
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 …
A classical measure is essentially a set function satisfying nonnegativity and countable additivity axioms. However, the additivity axiom of classical measure theory has been …
Some information and knowledge are usually represented by human language like “about 100km”,“approximately 39° C”,“roughly 80kg”,“low speed”,“middle age”, and “big size”. How …
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 …
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 …
CC Chou, LJ Liu, SF Huang, JM Yih, TC Han - Applied Soft Computing, 2011 - Elsevier
The airline service quality is an important issue in the international air travel transportation industry. Although a number of studies focus on the subject of airline service quality …
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 …