• KELLEY

  • Referenced in 581 articles [sw04829]
  • optimization methods for unconstrained and bound constrained minimization problems. The style of the book ... into two parts. The first part, occupying approximately 100 pages, is devoted to the optimization ... projection methods for the solution of bound constrained problems. All chapters conclude with a demonstration ... second part of the book, which is approximately 50 pages long, deals with the optimization...
  • SNOPT

  • Referenced in 480 articles [sw02300]
  • methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions ... based on a limited-memory quasi-Newton approximation to the Hessian of the Lagrangian...
  • CGAL

  • Referenced in 320 articles [sw00118]
  • data structures and algorithms like triangulations (2D constrained triangulations and Delaunay triangulations ... estimation of local differential properties, and approximation of ridges and umbilics), alpha shapes, convex hull...
  • Basc

  • Referenced in 4 articles [sw25969]
  • Basc: constrained approximation by semidefinite programming. This article details the theoretical grounds for a semidefinite...
  • MATISSE

  • Referenced in 25 articles [sw06311]
  • constrained linear systems. Matisse is based on the framework of abstracting linear systems using approximate...
  • redbKIT

  • Referenced in 94 articles [sw12977]
  • PDEs depending on several parameters and PDE-constrained optimization. The book presents a general mathematical ... proper orthogonal decomposition techniques, investigate their approximation properties and analyze offline-online decomposition strategies aimed...
  • CNOP

  • Referenced in 7 articles [sw00139]
  • present a generic package for resource constrained network optimization problems. We illustrate the flexibility ... four applications: route planning, curve approximation, minimum cost reliability constrained spanning trees and the table...
  • DEMORS

  • Referenced in 8 articles [sw02773]
  • robust algorithm able to solve difficult constrained multi-objective optimization problems at a moderate computational ... hybrid approach to approximate the Pareto front of a constrained multi-objective optimization problem while ... evolution is used to generate an initial approximation of the Pareto front. Then ... spread and quality of this initial approximation. To assess the performance of our proposed approach...
  • SQPlab

  • Referenced in 135 articles [sw05161]
  • implementation of the SQP algorithm for solving constrained optimization problems. The functions defining the problem ... iterations (hence QP solves) to find an approximate solution with a good precision (this...
  • ECHO

  • Referenced in 20 articles [sw22269]
  • approximate Riemann solver is used. The induction equation is treated by adopting the Upwind Constrained...
  • GPGCD

  • Referenced in 8 articles [sw06224]
  • method, the problem of approximate GCD is transferred to a constrained minimization problem, then solved...
  • GUSTAF

  • Referenced in 4 articles [sw18113]
  • shallow-water equations. This method approximates the nonlinearly constrained minimization problem by solving a series...
  • CONDOR

  • Referenced in 23 articles [sw02490]
  • CONDOR, a new parallel, constrained extension of Powell’s UOBYQA algorithm: Experimental results and comparison ... UOBYQA algorithm (Unconstrained Optimization BY Quadratical Approximation) [Math. Program ... results between UOBYQA, DFO and a parallel, constrained extension of UOBYQA that will be called...
  • FLEUR

  • Referenced in 3 articles [sw22272]
  • treated on the basis of the GW approximation [21,22] and ladder diagrams are included ... calculated in the constrained random phase approximation (cRPA...
  • ACCEPT

  • Referenced in 1 article [sw22894]
  • includes C/C++ type qualifiers for constraining approximation, a compiler analysis library that identifies regions...
  • RITUAL

  • Referenced in 4 articles [sw02121]
  • described. The problem is formulated as a constrained programming problem and is solved ... used to find an approximate solution to the constrained problem. The algorithm yields good results...
  • DSPCA

  • Referenced in 35 articles [sw04804]
  • examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix ... symmetric matrix, where cardinality is constrained, and derive a semidefinite programming based relaxation...
  • BVLS

  • Referenced in 4 articles [sw04345]
  • linear functionals of a model constrained to satisfy, in approximate l p -norm sense...
  • IMFIL

  • Referenced in 31 articles [sw04814]
  • filtering is a way to solve bound-constrained optimization problems for which derivative information ... search and then interpolates to get an approximation of the gradient. Implicit Filtering describes...
  • SmallK

  • Referenced in 2 articles [sw21816]
  • factorization (NMF). NMF is a constrained low rank approximation where a matrix is approximated...