Cluster Analysis is at the crossroad of many disciplines, and has numerous and diverse methods and applications. Mathematical Programming (together with gra...

We propose a new exact algorithm for the convex-quadratic bilevel programming problem, i.e, for problems with convex objective function and convex constrain...

Consider an assignment problem in which persons are qualified for some but usually not all of the jobs. Moreover, assume persons belong to given seniority c...

An overview is given, with new results, of mathematical models and algorithms for probabilistic logic, probabilistic entailment and various extensions. Anal...

Global optimization methods aim at finding the global optimum of a nonlinear and nonconvex function subject to nonlinear and nonconvex constraints. The main...

We study the generalization of Piyavskii's algorithm (1972), proposed by Mladineo (1986), for the global optimization of multivariate Lipschitz functions. I...

Given a set of logical sentences together with probabilities that these sentences are true, the probabilistic satisfiability (PSAT) problem consists, in it...

We present a method to compute valid concavity cuts for the linear maxmin programming problem. We consider a primal and a dual approach. In both cases the p...

A new paradigm for cluster analysis is outlined. It is called Sequential Clustering. Given a set <i>O</i> of <i>N</i> entities a best cluster of <i>K</i> ...

Le problème de la satisfaisabilité probabiliste (PSAT) consiste à déterminer, étant donné les probabilités de <i>m</i> événements (ou propositions logiques...

An <i>O</i> (<i>mn</i> log <i>n</i>) labeling algorithm is proposed for minimum sum of diameters bipartitioning of the vertex set of a weighted graph (with ...

Consider a set of logical sentences together with probabilities that they are true. These probabilities must satisfy certain conditions for this system to b...

The product positioning problem consists in choosing the attributes of a new product in such a way as to maximize its market share, i.e., to attract a maxi...

Lipschitz optimization solves global optimization problems in which the objective function and constraint left-hand sides may be given by oracles (or explic...

Much work has been devoted to the problem of finding maximum likelihood estimators for the three-parameter Weibull distribution. This problem has not been c...

Three main mathematical programming approaches have been followed to design exact algorithms for partitioning problems in cluster analysis, cutting-planes, ...

Dendrograms are widely used to represent graphically the clusters and partitions obtained with hierarchical clustering schemes. Espaliers are generalized de...

The minimum sum-of-stars (or <i>p</i>-median, or <i>p</i>-medianoïd) clustering problem consists in partitioning a given set of entities into <i>P</i> clust...

We propose a new branch-and-bound algorithm for the Satisfiability problem (SAT). A relaxation as well as a decomposition scheme are defined by using polyno...

A linear algorithm is proposed for a particular case of the satisfiability problem which strictly includes nested satisfiability. Recognition of this case c...