A global optimization procedure is proposed to find a line in the Euclidean three-dimensional space which minimizes the sum of distances to a given finite set of three-dimensional data points. Although we are using similar techniques as for location problems in two dimensions, it is shown that...

A new model for locating a competitive facility in the plane in a robust way is presented and embedded in the literature on robustness in facility location. Its mathematical properties are investigated and new sharp bounds for a deterministic method that guarantees the global optimum are derived...

Euclidean Minimum Sum-of-Squares Clustering amounts to finding p prototypes by minimizing the sum of the squared Euclidean distances from a set of points to their closest prototype. In recent years related clustering problems have been extensively analyzed under the assumption that the space is...

Most time series forecasting methods assume the series has no missing values. When missing values exist, interpolation methods, while filling in the blanks, may substantially modify the statistical pattern of the data, since critical features such as moments and autocorrelations are not...

Monetary Unit Sampling (MUS), also known as Dollar-Unit Sampling, is a popular sampling strategy in Auditing, in which all units are to be randomly selected with probabilities proportional to the book value. However, if units sizes have very large variability, no vector of probabilities exists...

In this note we address the problem of determining selection probabilities for multipurpose surveys, when the aim is the simultaneous minimization of variances for each variable under study. A characterization of the set of Pareto-optimal designs is given for designs with replacement and also...