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Optimization
editVolume 1
edit- Optimization (mathematics)
- Maxima and minima
- Steepest descent
- Linear programming
- Convex programming
- Second order cone programming
- Semidefinite programming
- Matrix (mathematics)
- Conic programming
- Geometric programming
- Monomials
- Integer programming
- Integer
- Quadratic programming
- Stochastic programming
- Combinatorial optimization
- Infinite-dimensional optimization
- Discrete mathematics
- Dimension
- Heuristic algorithm
- Metaheuristic
- Constraint satisfaction
- Artificial intelligence
- Automated reasoning
- Constraint programming
- Trajectory optimization
- Calculus of variations
- Optimal control
- Dynamic programming
- Bellman equation
- Mathematical programming with equilibrium constraints
- Variational inequalities
- Complementarity theory
- Multiobjective optimization
- Evolutionary Algorithm
- Evolutionary multi-modal optimization
- Dimensionless
- Response surfaces
- Optimization problem
- Computer vision
- System
- Mathematical model
- Constraint (mathematics)
- Domain (mathematics)
- Candidate solution
- Functional (mathematics)
- Convex set
- Global optimization
- Satisfiability problem
- Extreme value theorem
- Fermat's theorem (stationary points)
- Stationary point
- First derivative test
- Critical point (mathematics)
- Lagrange multiplier
- Karush-Kuhn-Tucker conditions
- Hessian matrix
- Second derivative test
- Envelope theorem
- Maximum theorem
- Conjugate gradient method
- Ellipsoid method
- Frank–Wolfe algorithm
- Interior point methods
- Line search
- Nelder-Mead method
- Newton's method in optimization
- Quasi-Newton methods
- Simplex method
- Subgradient method
- Convex function
- Ant colony optimization
- Bat algorithm
- Beam search
- Bees algorithm
- Differential evolution
- Dynamic relaxation
- Evolution strategy
- Firefly algorithm
- Genetic algorithms
- Harmony search
- Hill climbing
- IOSO
- Particle swarm optimization
- Quantum annealing
- Simulated annealing
- Stochastic tunneling
- Tabu search
- Engineering optimization
- Multidisciplinary design optimization
- Utility maximization problem
- Dual problem
- Expenditure minimization problem
- Operations research
- Linear complementarity problem
- Hamiltonian mechanics
- Pontryagin's minimum principle
- Karush–Kuhn–Tucker conditions
- Lagrangian mechanics
- Hessian (mathematics)
- Probability distribution
- Information entropy
- Saddle point
- Gradient descent
- Quasi-Newton method
- Gradient
- Stationary points
- Costate
- Convex optimization
- Lagrange multipliers on Banach spaces
- Function (mathematics)
- Joseph Louis Lagrange