" Numerical optimization " presents a comprehensive and up to date description of the most effective methods in continuous optimization. It responds to...
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" Numerical optimization " presents a comprehensive and up to date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. Drawing on their experiences in teaching, research, and consulting, the authors have produced a textbook that will be of interest to students and practitioners alike. Each chapter begins with the basics concepts and builds up gradually to the best techniques currently available. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. Above all, the authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.
Sommaire
Fundamentals of unconstrained optimization
Line search methods
Trust-region methods
Conjugate gradient methods
Practical Newton methods
Calculating derivates
Quasi-Newton methods
Large-scale Quasi-Newton and partially separable optimization
Nonlinear least-squares problems
Nonlinear equations
Theory of constrained optimization
Linear programming : the simplex method
Linear programming : interior-point methods
Fundamentals of algorithms for nonlinear constrained optimization
Quadratic programming
Penalty, Barrier, and augmented lagrangian methods