Numerical Optimization Book

General Introduction.- Part I: Unconstraint Problems: Basic Methods; Line-Searches; Newtonian Methods; Conjugate Gradient; Special Methods.- Part II: Nonsmooth Optimization: Some Theory of Nonsmooth Optimization; Some Methods in Nonsmooth Optimization; Bundle Methods. The Quest of Decent; Decomposition and Duality.- Part III: Newton's Methods in Constrained Optimization: Background; Local Methods for Problems with Equality Constraints; Local Methods for Problems with Equality and Inequality Constraints; Exact Penalization; Globalization by Line-Search; Quasi-Newton Versions.- Part IV: Interior-Point Algorithms for Linear and Quadratic Optimization: Linearly Constrained Optimization and Simplex Algorithm; Linear Monotone Complementary and Associated Vector Fields; Predictor-Corrector Algorithms; Non-Feasible Algorithms; Self-Duality; One-Step Methods; Complexity of Linear Optimization Problems with Integer Data; Karmarkar's Algorithm.- References.- Index.