In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization...

alternatives have been proposed. The popular Berndt–Hall–Hall–Hausman algorithm approximates the Hessian with the outer product of the expected gradient...

an optimization algorithm in the collection of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited...

formula is quite effective, but it was soon superseded by the Broyden–Fletcher–Goldfarb–Shanno formula, which is its dual (interchanging the roles of y and...

Preconditioning Broyden–Fletcher–Goldfarb–Shanno algorithm Davidon–Fletcher–Powell formula Nelder–Mead method Gauss–Newton algorithm Hill climbing Quantum...

such as Newton's method or quasi-Newton methods like the Broyden–Fletcher–Goldfarb–Shanno algorithm. The approach has been applied to solve a wide range of...

guaranteed.[citation needed] Davidon–Fletcher–Powell (DFP) algorithm Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm Henningsen, A.; Toomet, O. (2011)...

Optimization algorithms: Limited-memory BFGS (L-BFGS) (Stan's default optimization algorithm) Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) Laplace's...

Newton's method in optimization Davidon–Fletcher–Powell formula Broyden–Fletcher–Goldfarb–Shanno (BFGS) method Broyden, C. G. (1965). "A Class of Methods for...

specialization in logic Broyden–Fletcher–Goldfarb–Shanno algorithm, a method for solving nonlinear optimization problems Goldfarb Seligman & Co., the largest...

developers of the Broyden–Fletcher–Goldfarb–Shanno algorithm. In 1992, he and J. J. Forrest developed the steepest edge simplex method. Goldfarb is National...

Nonlinear conjugate gradient method Levenberg–Marquardt algorithm Broyden–Fletcher–Goldfarb–Shanno or BFGS method Differential evolution Pattern search (optimization)...

(suggested independently by Broyden, Fletcher, Goldfarb, and Shanno, in 1970), and its low-memory extension L-BFGS. The Broyden's class is a linear combination...

descent Broyden–Fletcher–Goldfarb–Shanno algorithm Conjugate gradient method L-BFGS (limited memory BFGS) Nelder–Mead method Wolfe conditions Fletcher, R.;...

quasi-Newton method, such as that due to Davidon, Fletcher and Powell or Broyden–Fletcher–Goldfarb–Shanno (BFGS method) an estimate of the full Hessian ∂...

In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve...

Column generation or delayed column generation is an efficient algorithm for solving large linear programs. The overarching idea is that many linear programs...

computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems...

but very robust. The technique derives its name from the fact that the algorithm maintains the function values for four points whose three interval widths...

In computer science, the Edmonds–Karp algorithm is an implementation of the Ford–Fulkerson method for computing the maximum flow in a flow network in...

technique which belongs to the family of local search. It is an iterative algorithm that starts with an arbitrary solution to a problem, then attempts to...

Davidon–Fletcher–Powell formula — update of the Jacobian in which the matrix remains positive definite Broyden–Fletcher–Goldfarb–Shanno algorithm — rank-two...

Dantzig's simplex algorithm (or simplex method) is a popular algorithm for linear programming.[failed verification] The name of the algorithm is derived from...

The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional gradient...

A greedy algorithm is any algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. In many problems, a...

computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems...

Dinic's algorithm or Dinitz's algorithm is a strongly polynomial algorithm for computing the maximum flow in a flow network, conceived in 1970 by Israeli...

IPMs) are algorithms for solving linear and non-linear convex optimization problems. IPMs combine two advantages of previously-known algorithms: Theoretically...

method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes)...

Branch and bound algorithms have a number of advantages over algorithms that only use cutting planes. One advantage is that the algorithms can be terminated...