We consider the solution of derivative-free optimization problems with continuous, integer, discrete and categorical variables in the context of costly black...

Global optimization problems are very hard to solve, especially when the nonlinear constraints are highly nonconvex, which can result in a large number of di...

We study X-ray tomograqphic reconstruction using statistical methods. The problem is expressed in cylindrical coordinates, which yield significant computatio...

The particularities of the aircraft parts riveting process simulation necessitate the solution of a large amount of contact problems. We propose a primal-dua...

Nanoparticle-based drug delivery is a promising method to increase the therapeutic index of anti-cancer agents with low median toxic dose. The delivery effic...

The problem of output stabilization is studied for a class of linear hybrid systems subject to signal uncertainties: linear impulsive systems under dwell-t...

This paper proposes a hierarchical decision making model for a coupled planning and operation problem of an advanced microgrid. The proposed model, is formul...

In this article we consider a difficult combinatorial optimization problem arising from the operation of a system for testing electronic circuit boards (EC...

We propose an iterative method named LSLQ for solving linear least-squares problems $A x \approx b$ of any shape. The method is based on the Golub and K...

For pattern-based simulation methods such as SIMPAT, filtersim, wavesim, ect, patterns are stored by scanning a training image with a sliding template. Dimen...

Locally weighted regression combines the advantages of polynomial regression and kernel smoothing. We present three ideas for appropriate and effective use...

The $k$-means is a benchmark algorithm used in cluster analysis. It belongs to the large category of heuristics based on location-allocation steps that ...

The balanced clustering problem consists of partitioning a set of $n$ objects into $K$ equal-sized clusters as long as $n$ is a multiple of `(K...

For positive definite linear systems (or semidefinite consistent systems), we use Gauss-Radau quadrature to obtain a cheaply computable upper bound on the ...

Blackbox optimization problems are often contaminated with numerical noise, and direct search methods such as the Mesh Adaptive Direct Search (MADS) algorit...

NLP.py is a programming environment to model continuous optimization problems and to design computational methods in the high-level and powerful Python l...

In the present paper, we prove lower and upper bounds for each of the ratios $GA/\delta$, $GA/\overline{d}$ and $\Delta$, in terms of the order `...

This paper presents a numerical investigation of the non-hierarchical formulation of Analytical Target Cascading (ATC) for coordinating distributed multidisc...

This paper proposes a bilevel formulation for a coupled planning and operation problem of an advanced microgrid. The proposed model, recast as a mathematical...

We describe a collection of linear systems generated during the iterations of an interior-point method for convex quadratic optimization. As the iteration...