User:Eigen Axon/Books/Optimization

Emphasizing Evolutionary Algorithm

 * Introduction
 * Mathematical optimization
 * Feasible region
 * Global optimum
 * Local optimum
 * Maxima and minima
 * Slack variable
 * Continuous optimization
 * Discrete optimization
 * Active set method
 * Candidate solution
 * Constraint (mathematics)
 * Constrained optimization
 * Binary constraint
 * Corner solution


 * Linear Programming
 * Linear programming
 * Basic solution (linear programming)
 * Hilbert basis (linear programming)
 * Linear inequality
 * Vertex enumeration problem
 * Simplex algorithm
 * Bland's rule
 * Klee–Minty cube
 * Criss-cross algorithm
 * Big M method
 * Interior point method
 * Ellipsoid method
 * Karmarkar's algorithm
 * Mehrotra predictor–corrector method
 * Column generation
 * K-approximation of k-hitting set
 * Linear complementarity problem
 * Benders' decomposition
 * Dantzig–Wolfe decomposition
 * Theory of two-level planning
 * Variable splitting
 * Fourier–Motzkin elimination
 * LP-type problem


 * Convex Optimization
 * Convex optimization
 * Quadratic programming
 * Linear least squares (mathematics)
 * Total least squares
 * Frank–Wolfe algorithm
 * Sequential minimal optimization
 * Bilinear program
 * Basis pursuit
 * Basis pursuit denoising
 * In-crowd algorithm
 * Linear matrix inequality
 * Conic optimization
 * Semidefinite programming
 * Second-order cone programming
 * Sum-of-squares optimization
 * Bregman method
 * Proximal gradient method
 * Subgradient method
 * Biconvex optimization


 * Nonlinear Programming
 * Nonlinear programming
 * Geometric programming
 * Signomial
 * Posynomial
 * Quadratically constrained quadratic program
 * Linear-fractional programming
 * Fractional programming
 * Nonlinear complementarity problem
 * Least squares
 * Non-linear least squares
 * Gauss–Newton algorithm
 * Berndt–Hall–Hall–Hausman algorithm
 * Generalized Gauss–Newton method
 * Levenberg–Marquardt algorithm
 * Iteratively reweighted least squares
 * Partial least squares regression
 * Non-linear iterative partial least squares
 * Golden section search
 * Successive parabolic interpolation
 * Mathematical programming with equilibrium constraints
 * Descent direction
 * Guess value
 * Line search
 * Backtracking line search
 * Wolfe conditions
 * Gradient method
 * Gradient descent
 * Stochastic gradient descent
 * Derivation of the conjugate gradient method
 * Conjugate gradient method
 * Biconjugate gradient method
 * Nonlinear conjugate gradient method
 * Landweber iteration
 * Successive linear programming
 * Sequential quadratic programming
 * Newton's method in optimization
 * Coordinate descent
 * Adaptive coordinate descent
 * Random coordinate descent
 * Nelder–Mead method
 * Pattern search (optimization)
 * Powell's method
 * Rosenbrock methods
 * Augmented Lagrangian method
 * Ternary search
 * Tabu search
 * Guided Local Search
 * LIONsolver
 * MM algorithm
 * Least absolute deviations
 * Expectation–maximization algorithm
 * Ordered subset expectation maximization
 * Adaptive projected subgradient method
 * Nearest neighbor search
 * Space mapping


 * Infinite-Dimension Optimization
 * Optimal control
 * Pontryagin's minimum principle
 * Costate equations
 * Hamiltonian (control theory)
 * Linear-quadratic regulator
 * Linear-quadratic-Gaussian control
 * Optimal projection equations
 * Algebraic Riccati equation
 * Bang–bang control
 * Covector mapping principle
 * Differential dynamic programming
 * DNSS point
 * Legendre–Clebsch condition
 * Pseudospectral optimal control
 * Bellman pseudospectral method
 * Chebyshev pseudospectral method
 * Flat pseudospectral method
 * Gauss pseudospectral method
 * Legendre pseudospectral method
 * Pseudospectral knotting method
 * Ross–Fahroo pseudospectral method
 * Ross–Fahroo lemma
 * Ross' π lemma
 * Sethi model
 * Infinite-dimensional optimization
 * Semi-infinite programming
 * Shape optimization
 * Topology optimization
 * Topological derivative
 * Generalized semi-infinite programming


 * Stochastic
 * Stochastic optimization
 * Stochastic programming
 * Stochastic approximation
 * Markov decision process
 * Partially observable Markov decision process
 * Probabilistic-based design optimization
 * Robust optimization
 * Wald's maximin model
 * Scenario optimization
 * Random optimization
 * Random search
 * Simulated annealing
 * Adaptive simulated annealing
 * Great Deluge algorithm
 * Mean field annealing
 * Bayesian optimization
 * Luus–Jaakola
 * Stochastic tunneling
 * Harmony search
 * Monte Carlo method
 * Direct simulation Monte Carlo
 * Quasi-Monte Carlo method
 * Markov chain Monte Carlo
 * Metropolis–Hastings algorithm
 * Pseudo-random number sampling
 * Variance reduction


 * Evolutionary Algorithms
 * Artificial intelligence
 * Metaheuristic
 * Evolutionary algorithm
 * Fitness function
 * Evolutionary computation
 * Evolutionary programming
 * Gene expression programming
 * Differential evolution
 * Genetic algorithm
 * Genetic programming
 * Genetic algorithms in economics
 * MCACEA
 * Simultaneous perturbation stochastic approximation
 * Evolution strategy
 * Neuroevolution
 * Learning classifier system
 * Swarm intelligence
 * Ant colony optimization algorithms
 * Artificial bee colony algorithm
 * Particle swarm optimization
 * Cuckoo search
 * Bees algorithm
 * Artificial immune system
 * Bat algorithm
 * Glowworm swarm optimization
 * Self-propelled particles
 * Stochastic diffusion search
 * Multi-swarm optimization
 * Firefly algorithm
 * Memetic algorithm