Engineering (engineering design, digital design)

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214 results — page 5 of 11

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Derivative-free optimization (DFO) is the mathematical study of the optimization algorithms that do not use derivatives. One branch of DFO focuses on model-...

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The mesh adaptive direct search (MADS) algorithm is designed for blackbox optimization problems for which the functions defining the objective and the constr...

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We propose an infeasible interior-point algorithm for constrained linear least-squares problems based on the primal-dual regularization of convex program...

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We investigate surrogate-assisted strategies for global derivative-free optimization using the mesh adaptive direct search MADS blackbox optimization algorit...

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We propose a factorization-free method for equality-constrained optimization based on a problem in which all constraints are systematically regularized. ...

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For optimization problems involving many nonlinear inequality constraints, we extend the bound-constrained (BCL) and linearly-constrained (LCL) augmented-La...

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Despite the lack of theoretical and practical convergence support, the Nelder-Mead (NM) algorithm is widely used to solve unconstrained optimization proble...

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

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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...

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

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

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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...

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

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

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

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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...

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

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

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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 ...

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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...

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