The selection of a project among a set of possible alternatives is a difficult task decision makers have to face. Difficulties in selecting a project arise because of the different goals involved and because of the large number of attributes to consider. Our approach is based upon a fuzzy extension of the Analytic Hierarchy Process (AHP). This paper focuses on the constraints that have to be co...

Since Markowitz’s seminal work on the meanvariance model in modern portfolio theory, many studies have been conducted on computational techniques and recently meta-heuristics for portfolio selection problems. In this work, we propose and investigate a new hybrid algorithm integrating the population based incremental learning and differential evolution algorithms for the portfolio selection prob...

One of the important issues in data warehouse development is the selection of a set of views to materialize in order to accelerate a large number of on-line analytical processing (OLAP) queries. The maintenance-cost view-selection problem is to select a set of materialized views under certain resource constraints for the purpose of minimizing the total query processing cost. However, the search...

Feature selection is an important problem in machine learning and data mining. We consider the problem of selecting features under the budget constraint on the feature subset size. Traditional feature selection methods suffer from the "monotonic" property. That is, if a feature is selected when the number of specified features is set, it will always be chosen when the number of specified featur...

Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of items of interest, subject to a space constraint. We show that in many important applications, one faces variants of this basic problem, in which the individual items are sets themselves, and each set is associated with ...

High-dimensional feature selection has become increasingly crucial for seeking parsimonious models in estimation. For selection consistency, we derive one necessary and sufficient condition formulated on the notion of degree-of-separation. The minimal degree of separation is necessary for any method to be selection consistent. At a level slightly higher than the minimal degree of separation, se...