This book has two main objectives: ---to provide a concise introduction to nonlinear optimization methods, which can be used as a textbook at a graduate or upper undergraduate level; - -to collect and organize selected important-topics on optimization algorithms, not easily found in textbooks, which can provide material for advanced courses or can serve as a reference text for self-study and research. The basic material on unconstrained and constrained optimization is organized into two blocks of chapters: ---basic theory and optimality conditions ---unconstrained and constrained algorithms. These topics are treated in short chapters that contain the most important results in theory -and algorithms, in a way that, in the authors- experience, is suitable for introductory courses. -A third block of chapters addresses methods that are of increasing interest for solving difficult optimization problems. Difficulty can be typically due to the high nonlinearity of the objective function, ill-
