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Menu systems are key components in modern graphical user interfaces (GUIs), either for traditional desktop applications, or for the latest web applications. The design of interface layout must consider different aspects resulting in a trade-off between often conflicting requirements. This trade-off is aimed at making effective use of interfaces in order to meet user preferences and to conform to standard guidelines at the same time. Assuming we are able to quantify such a trade-off, the problem of finding a menu system able to maximize it figures as a combinatorial optimization problem. In this paper we investigate the application of genetic algorithms as a viable approach to identifying solutions that can be used as a starting point for further fine-tuning. [ABSTRACT FROM AUTHOR]

The OWA weighting vector and the fuzzy quantifiers are strictly related. An intuitive way for shaping a monotonic quantifier, is by means of the threshold that makes a separation between the regions of what is satisfactory and what is not. Therefore, the characteristics of a threshold can be directly related to the OWA weighting vector and to its metrics: the attitudinal character and the entropy (or dispersion). Generally these two metrics are supposed to be independent, although some limitations in their value come when they are considered jointly. In this paper we argue that these two metrics are strongly related by the definition of quantifier threshold, and we show how they can be used jointly to verify and validate a quantifier and its threshold. [ABSTRACT FROM AUTHOR]