The effect of ranking and binary tournament selection on the distribution of fitnesses and genetic correlation is calculated for a finite population. The results are different for continuous and discrete fitness functions. Results for both situations are obtained. These exact results are compared to a previously obtained approximation up to the third cumulant and shown to be in good agreement. ...

Beginning with a representational framework of which genetic algorithms are a special case, the ranking and tournament selection schemes are defined and formalized as mathematical functions. The main result is that ranking and tournament selection are diffeomorphisms of the representation space. Explicit algorithms are also developed for computing their inverses.

Vendor performance plays a key role in price, quality, timely delivery and service in achieving the goals of the supply chain. Given this, today's supplier performance has become a critical element in the success or failure of a company. In this study, an idealized planning model with multi-criteria decision-making approach with network analysis tool based on the expansion of fuzzy quality func...

High dimensionality and class imbalance are two main problems that affect the quality of training datasets in software defect prediction, resulting in inefficient classification models. Feature selection and data sampling are often used to overcome these problems. Feature selection is a process of choosing the most important attributes from the original data set. Data sampling alters the data s...

The research on supplier selection is abundant and the works usually only consider the critical success factors in the buyer–supplier relationship. However, the negative aspects of the buyer–supplier relationship must also be considered simultaneously. In this paper we propose a comprehensive model for ranking an arbitrary number of suppliers, selecting a number of them and allocating a quota o...

An attractive property of attribute-value grammars is their reversibility. Attribute-value grammars are usually coupled with separate statistical components for parse selection and fluency ranking. We propose reversible stochastic attribute-value grammars, in which a single statistical model is employed both for parse selection and fluency ranking.