• # KELLEY

• Referenced in 592 articles [sw04829]
• introduction to optimization methods for unconstrained and bound constrained minimization problems. The style ... Gauss-Newton method for the solution of nonlinear least squares problems. Both, overdetermined and underdetermined...
• # tn

• Referenced in 126 articles [sw05140]
• solution of large-scale unconstrained minimization problems. It is shown how the equivalent Lanczos characterization ... interpolates between the direction defined by a nonlinear conjugate-gradient-type method and a modified...
• # Algorithm 738

• Referenced in 7 articles [sw08077]
• software package for finding the unconstrained minimizer of a nonlinear function of n variables ... between a recently developed “tensor method” for unconstrained optimization and an analogous standard method based...
• # Algorithm 739

• Referenced in 4 articles [sw04404]
• software package for finding the unconstrained minimizer of a nonlinear function of $n$ variables ... between a recently developed “tensor method” for unconstrained optimization and an analogous standard method based...
• # Complex Optimization Toolbox

• Referenced in 22 articles [sw14744]
• Included are generalized algorithms for unconstrained nonlinear optimization: nonlinear conjugate gradient and limited-memory BFGS ... search or dogleg trust region, nonlinear least squares: minimization of vector-, matrix- or tensor-valued...
• # CONMIN

• Referenced in 50 articles [sw04741]
• form, for the solution of linear or nonlinear constrained optimization problems. The basic optimization algorithm ... efficient solution of constrained problems, unconstrained function minimization problems may also be solved...

• Referenced in 4 articles [sw13387]
• FORTRAN program for nonlinear constrained (or unconstrained) function minimization. The optimization process is segmented into...
• # STENMIN

• Referenced in 2 articles [sw00917]
• describe a new package for minimizing an unconstrained nonlinear function where the Hessian is large ... incorporation of an entirely new way of minimizing the tensor model that makes it suitable ... standard Newton method for solving large, sparse unconstrained optimization problems...
• # GUSTAF

• Referenced in 4 articles [sw18113]
• approximates the nonlinearly constrained minimization problem by solving a series of unconstrained minimization problems. Program ... water equations. According to the number of nonlinear quasi-Newton (QN) iterations performed at each...
• # SOLVEX

• Referenced in 1 article [sw16222]
• numerical algorithms for solving unconstrained, nonlinear constrained, global minimization, and multi-criteria optimization problems...
• # NEWSUMT

• Referenced in 1 article [sw18772]
• Fortran program for inequality constrained function minimization. A computer program written in FORTRAN subroutine form ... solution of linear and nonlinear constrained and unconstrained function minimization problems is presented. The algorithm...
• # csminwel

• Referenced in 3 articles [sw05280]
• Matlab programs that solve nonlinear equations and minimize using quasi-Newton with BFGS update ... that do about the same thing. The minimizer can negotiate discontinuous ”cliffs” without getting stuck ... unconstrained optimization and nonlinear equations-solving. It also contains some auxiliary m files. csminwel: minimization...
• # SpeeDP

• Referenced in 4 articles [sw07003]
• rank semidefinite programming (LRSDP) relaxations of unconstrained ${-1,1}$ quadratic problems (or, equivalently ... formulated as the non-convex nonlinear programming problem of minimizing a quadratic function subject ... equivalence of the LRSDP problem with the unconstrained minimization of a new merit function...
• # Poblano

• Referenced in 9 articles [sw04186]
• toolbox of large-scale algorithms for unconstrained nonlinear optimization problems. The algorithms in Poblano require ... analysis, chemometrics, etc.). Poblano optimizers find local minimizers of scalar-valued objective functions taking vector...
• # NLP

• Referenced in 3 articles [sw07786]
• General purpose nonlinear programming package. This paper tries to make three steps towards more efficient ... different algorithms applied to a specific minimization problem. All the algorithms use similar, problem-dependent ... criteria. Secondly, an efficient standard algorithm for unconstrained optimization without using derivatives is described ... maximum accuracy. Thirdly, the user of the nonlinear programming package has the option to leave...
• # BBVSCG

• Referenced in 6 articles [sw00069]
• approximation to a local minimum of a nonlinear function f(x). Here ... continuous second derivatives. As with almost all minimization algorithms, there is no attempt made ... Shanno} and {it K. H. Phua} [Minimization of unconstrained multivariate functions, ibid...
• # ACGSSV

• Referenced in 8 articles [sw20836]
• value of this parameter is determined by minimizing the distance between the symmetrical scaled Perry ... given both for uniformly convex and general nonlinear functions under the exact or the Wolfe ... line search. Using a set of 800 unconstrained optimization test problems, of different structure...
• # Rice Vector Library

• Referenced in 2 articles [sw20169]
• function,...) of calculus in Hilbert space with minimal implementation dependence, and providing standardized interfaces behind ... Newton’s method for nonlinear equations and constrained and unconstrained optimization, may be expressed purely...