Category:Optimization algorithms and methods

• List of algorithms

A

• Active-set method
• Adaptive coordinate descent
• Adaptive dimensional search
• Adaptive simulated annealing
• Alpha–beta pruning
• Auction algorithm
• Augmented Lagrangian method
• Automatic label placement

B

• Backtracking line search
• Bacterial colony optimization
• Basin-hopping
• Benson's algorithm
• Berndt–Hall–Hall–Hausman algorithm
• Bin packing problem
• Bland's rule
• BOBYQA
• Branch and bound
• Branch and cut
• Branch and price
• Bregman Lagrangian
• Bregman method
• Broyden–Fletcher–Goldfarb–Shanno algorithm

C

• CMA-ES
• COBYLA
• Coffman–Graham algorithm
• Column generation
• Communication-avoiding algorithms
• Constructive heuristic
• Crew scheduling
• Criss-cross algorithm
• Critical line method
• Cross-entropy method
• Cunningham's rule
• Cutting-plane method

D

• DATADVANCE
• Derivation of the conjugate gradient method
• Derivative-free optimization
• Destination dispatch
• Divide-and-conquer algorithm
• Dykstra's projection algorithm
• Dynamic programming

E

• Evolutionary algorithm
• Evolutionary programming
• Exact algorithm
• Expectation–maximization algorithm
• Extremal optimization

F

• Fernandez’s method
• Fireworks algorithm
• Fly algorithm
• Fourier–Motzkin elimination
• Fractional programming

G

• Gauss–Newton algorithm
• Generalized iterative scaling
• Genetic algorithms in economics
• Genetic improvement (computer science)
• Gradient descent
• Gradient method
• Graduated optimization
• Great Deluge algorithm
• Greedy algorithm
• Greedy triangulation
• Guided Local Search

H

• Hyper-heuristic

I

• In-crowd algorithm
• Interior-point method
• Interval contractor
• IOSO
• Software:IPOPT
• Iterated conditional modes
• Iterated local search

J

• Job shop scheduling

K

• Kantorovich theorem
• Karmarkar's algorithm
• Killer heuristic

L

• Lawler's algorithm
• Learning rate
• Least squares
• Lemke's algorithm
• Level-set method
• Levenberg–Marquardt algorithm
• Limited-memory BFGS
• LINCOA
• Line search
• Linear-fractional programming
• Lloyd's algorithm
• Local convergence
• Local search (optimization)
• Luus–Jaakola

M

• Matheuristics
• Matrix chain multiplication
• Maximum subarray problem
• MCS algorithm
• Mehrotra predictor–corrector method
• MM algorithm

N

• Natural evolution strategy
• Negamax
• Nelder–Mead method
• Network simplex algorithm
• Newton's method
• Newton's method in optimization
• NEWUOA
• Nonlinear conjugate gradient method
• Nonlinear programming

O

• Odds algorithm
• Ordered subset expectation maximization

P

• Parallel metaheuristic
• Parametric programming
• Pattern search (optimization)
• Penalty method
• Powell's method
• Software:PSeven

Q

• Quadratic programming
• Quantum annealing
• Quasi-Newton inverse least squares method
• Quasi-Newton least squares method
• Quasi-Newton method

R

• Random optimization
• Random search
• Robust fuzzy programming
• Rosenbrock methods
• Ruzzo–Tompa algorithm

S

• Search-based software engineering
• Second-order cone programming
• Semidefinite embedding
• Sequential linear-quadratic programming
• Sequential minimal optimization
• Sequential quadratic programming
• Simplex algorithm
• Simulated annealing
• Simultaneous perturbation stochastic approximation
• Space allocation problem
• Space mapping
• Special ordered set
• Spiral optimization algorithm
• Stochastic dynamic programming
• Stochastic gradient Langevin dynamics
• Stochastic hill climbing
• Stochastic programming
• Subgradient method
• Successive linear programming
• Successive parabolic interpolation
• Symmetric rank-one

T

• Ternary search
• TOLMIN (optimization software)
• Tree rearrangement
• Truncated Newton method
• Trust region

U

• UOBYQA

V

• Very large-scale neighborhood search

Z

• Zadeh's rule
• Zionts–Wallenius method