# Engineering (engineering design, digital design)

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### 224 results — page 5 of 12

We build upon Estrin et al. (2019) to develop a general constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletch...

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The minimum residual method (MINRES) of Paige and Saunders (1975), which is often the method of choice for symmetric linear systems, is a generalization of t...

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We propose an iterative method named USYMLQR for the solution of symmetric saddle-point systems that exploits the orthogonal tridiagonalization method of Sa...

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We propose a regularization method for nonlinear least-squares problems with equality constraints. Our approach is modeled after those of Arreckx and Orban ...

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The present work is in a context of derivative-free optimization involving direct search algorithms guided by surrogate models of the original problem. The...

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In the interest of full disclosure, the reader is advised that I am biased positively towards the book considered here as I have collaborated with its first ...

BibTeX referenceImplementing a smooth exact penalty function for equality-constrained nonlinear optimization

We develop a general equality-constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletcher (1970). Although it was ...

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Algorithms for finding sparse solutions of underdetermined systems of linear equations have been the subject of intense interest in recent years, sparked b...

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We describe LNLQ for solving the least-norm problem `\(\min\ \|x\|\)`

subject to `\(Ax=b\)`

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Craig's method is known to be equivalent to applying the conjug...

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. ...

BibTeX referenceStabilized optimization via an NCL algorithm

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...

BibTeX referenceCCGO: Fast heuristic global optimization

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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