Category:Optimization algorithms

An optimization algorithm is a numerical method or algorithm for finding a value x such that f(x) is as small (or as large) as possible, for a given function f, possibly with some constraints on x. Here, x can be a scalar or vector of continuous or discrete values. If x is continuous, then the study of the algorithm is part of numerical analysis.

Subcategories

There is 1 subcategory to this category.

E

• Evolutionary algorithms

Articles in category "Optimization algorithms"

There are 28 articles in this category.

Automatic label placement B Boruvka's algorithm Branch and bound D Delayed column generation Dynamic programming E Evolutionary algorithm Expectation-maximization algorithm G Gauss-Newton algorithm Gradient descent

H Hill climbing K Kruskal's algorithm L Levenberg-Marquardt algorithm Local search M Matrix chain multiplication Minimax N Negamax Newton's method Newton's method in optimization P Parallel tempering

P cont. Prim's algorithm R Random optimization Random-restart hill climbing S Simplex algorithm Simulated annealing Stochastic gradient descent Stochastic programming Stochastic tunneling Swarm intelligence