Deprecated: $wgMWOAuthSharedUserIDs=false is deprecated, set $wgMWOAuthSharedUserIDs=true, $wgMWOAuthSharedUserSource='local' instead [Called from MediaWiki\HookContainer\HookContainer::run in /var/www/html/w/includes/HookContainer/HookContainer.php at line 135] in /var/www/html/w/includes/Debug/MWDebug.php on line 372
Study on a supermemory gradient method for the minimization of functions - MaRDI portal

Study on a supermemory gradient method for the minimization of functions

From MaRDI portal
Publication:2532077

DOI10.1007/BF00930579zbMath0172.19002OpenAlexW2030071347MaRDI QIDQ2532077

A. V. Levy, E. E. Cragg

Publication date: 1969

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00930579




Related Items

Generalized conjugate directionsGlobal convergence of modified HS conjugate gradient methodGlobal convergence of a memory gradient method for unconstrained optimizationNew conjugate gradient-like methods for unconstrained optimizationA new class of supermemory gradient methodsStrong global convergence of an adaptive nonmonotone memory gradient methodA gradient-related algorithm with inexact line searchesOn the convergence of a new hybrid projection algorithmAn optimal subgradient algorithm with subspace search for costly convex optimization problemsA local MM subspace method for solving constrained variational problems in image recoveryMemory gradient method for multiobjective optimizationConvergence of supermemory gradient methodA generalized super-memory gradient projection method of strongly sub-feasible directions with strong convergence for nonlinear inequality constrained optimizationGlobal convergence of a memory gradient method without line searchMemory gradient method with Goldstein line searchConjugate gradient methods using value of objective function for unconstrained optimizationA supermemory gradient projection algorithm for optimization problems with nonlinear constraintsA new descent algorithm with curve search ruleGeneralized memory gradient projection method for non-linear programming with non-linear equality and in-equality constraintsSupermemory descent methods for unconstrained minimizationOn memory gradient method with trust region for unconstrained optimizationA heuristic iterated-subspace minimization method with pattern search for unconstrained optimizationApproximation methods for the unconstrained optimizationExtensions of CGS algorithms: Generalized least-square solutionsA nonmonotone supermemory gradient algorithm for unconstrained optimizationThe Topkis-Veinott algorithm for solving nonlinear programs with lower and upper bounded variablesOptimal simultaneous maximuma posterioriestimation of states, noise statistics and parameters I. AlgorithmNumerical experiments on quadratically convergent algorithms for function minimizationTesting a Class of Methods for Solving Minimization Problems with Simple Bounds on the VariablesQuadratically convergent algorithms and one-dimensional search schemesNumerical experiments on dual matrix algorithms for function minimizationPseudo-conjugate directions for the solution of the nonlinear unconstrained optimization problem on a parallel computer



Cites Work