Langbahn Team – Weltmeisterschaft

Template:Optimization algorithms

Optimization: Algorithms, methods, and heuristics

Unconstrained nonlinear

Convergence	Trust region Wolfe conditions
Quasi–Newton	Berndt–Hall–Hall–Hausman Broyden–Fletcher–Goldfarb–Shanno and L-BFGS Davidon–Fletcher–Powell Symmetric rank-one (SR1)
Other methods	Conjugate gradient Gauss–Newton Gradient Mirror Levenberg–Marquardt Powell's dog leg method Truncated Newton

Newton's method

Graph of a strictly concave quadratic function with unique maximum. — Optimization computes maxima and minima.

Constrained nonlinear

General	Barrier methods Penalty methods
Differentiable	Augmented Lagrangian methods Sequential quadratic programming Successive linear programming

Convex optimization

Convex
minimization

Linear and
quadratic

Interior point	Affine scaling Ellipsoid algorithm of Khachiyan Projective algorithm of Karmarkar
Basis-exchange	Simplex algorithm of Dantzig Revised simplex algorithm Criss-cross algorithm Principal pivoting algorithm of Lemke Active-set method

Paradigms

Graph
algorithms

Minimum spanning tree	Borůvka Prim Kruskal

Shortest path	Bellman–Ford SPFA Dijkstra Floyd–Warshall

Metaheuristics
Evolutionary algorithm Hill climbing Local search Parallel metaheuristics Simulated annealing Spiral optimization algorithm Tabu search

Software

Quelle: http://en.wikipedia.org/wiki/Template:Optimization_algorithms