About the Book
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 183. Chapters: P versus NP problem, Pareto efficiency, Optimization, Operations research, Genetic algorithm, Least squares, Dynamic programming, Genetic programming, Semi-continuity, Quadratic programming, Random optimization, Calculus of variations, Lagrange multiplier, Optimal design, Metaheuristic, Optimal control, Non-linear least squares, NP-complete, Oriented matroid, No free lunch in search and optimization, Ordinal optimization, Multidisciplinary design optimization, Distributed constraint optimization, Bellman equation, Hyper-heuristic, Nearest neighbor search, Semidefinite programming, Least absolute deviations, Robust optimization, Starmad, Klee-Minty cube, Wald's maximin model, Geometric median, Maxima and minima, Compressed sensing, Google matrix, Linear complementarity problem, Trajectory optimization, Quasiconvex function, Differential evolution, Multi-objective optimization, Wing shape optimization, Convex optimization, Jeep problem, Response surface methodology, Backward induction, Dead-end elimination, Karush-Kuhn-Tucker conditions, Energy minimization, Topology optimization, Subgradient method, Level set method, MPS, AMPL, Job shop scheduling, APMonitor, Nonlinear programming, Pontryagin's minimum principle, Odds algorithm, Dual problem, Meta-optimization, Linear-fractional programming, Goal programming, Variational Monte Carlo, Maximum theorem, Stress majorization, DNSS point, Farkas' lemma, Global optimization, Stochastic programming, Lloyd's algorithm, Paradiseo, Dantzig-Wolfe decomposition, Chebyshev center, Pseudoconvex function, Optimal stopping, Subderivative, Mathematical Programming Society, Pattern search, Lazy caterer's sequence, Second-order cone programming, Optimal substructure, Rosenbrock function, Newsvendor, Wolfe conditions, Database tuning, Complementarity theory, Trust region, ..
