Category:Optimization algorithms and methods

D

• Decomposition methods‎ (8 P)
• Dynamic programming‎ (48 P)

E

• Evolutionary algorithms‎ (4 C, 50 P)
• Exchange algorithms‎ (10 P)

G

• Gradient methods‎ (20 P)

L

• Least squares‎ (40 P)
• Linear programming‎ (1 C, 58 P)

M

• Metaheuristics‎ (3 C, 14 P)

O

• Optimal scheduling‎ (23 P)

Q

• Quasi-Newton methods‎ (7 P)

• List of algorithms

A

• Active-set method
• Adaptive coordinate descent
• Adaptive dimensional search
• Adaptive simulated annealing
• Affine scaling
• Alpha–beta pruning
• Ant colony optimization algorithms
• Auction algorithm
• Augmented Lagrangian method
• Automatic label placement

B

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

C

• Chambolle-Pock algorithm
• CMA-ES
• Column generation
• Communication-avoiding algorithm
• Constructive heuristic
• Crew scheduling
• Criss-cross algorithm
• Critical line method
• Cross-entropy method
• Cunningham's rule
• Cutting-plane method

D

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

E

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

F

• Fernandez's method
• Fireworks algorithm
• Fitness function
• Fly algorithm
• Fourier–Motzkin elimination
• Fractional programming
• Frank–Wolfe algorithm

G

• Gauss–Newton algorithm
• Generalized iterative scaling
• Genetic algorithms in economics
• Genetic improvement (computer science)
• Golden-section search
• Gradient descent
• Gradient method
• Graduated optimization
• Great deluge algorithm
• Greedy algorithm
• Greedy triangulation
• Guided local search
• Guillotine cutting
• Guillotine partition

H

• HiGHS optimization solver
• Hyper-heuristic

I

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

K

• Kantorovich theorem
• Karmarkar's algorithm
• Killer heuristic

L

• Learning rate
• Least squares
• Least-squares spectral analysis
• Lemke's algorithm
• Level-set method
• Levenberg–Marquardt algorithm
• Lexicographic max-min optimization
• Lexicographic optimization
• Limited-memory BFGS
• 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
• Method of moving asymptotes
• Minimax
• Mirror descent
• MM algorithm
• Multiple subset sum

N

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

O

• Odds algorithm
• Optimal kidney exchange
• OR-Tools
• Ordered subset expectation maximization

P

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

Q

• Quadratic programming
• Quantum annealing

R

• Random optimization
• Random search
• Mauricio Resende
• 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
• Social cognitive optimization
• 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

T

• Ternary search
• Tree rearrangement
• Truncated Newton method
• Trust region

V

• Very large-scale neighborhood search

W

• Welfare maximization

Z

• Zadeh's rule
• Zionts–Wallenius method