This books provides a comprehensive treatment of all different kinds of numerical methods developed for nonsmooth optimization (NSO). The book covers both traditional methods and the methods developed to utilize special structures of problems. Part I presents general methods including traditional NSO, large-scale problems as well as second order and stochastic methods. Part II is dedicated to methods for structured problems, while Part III deals with special problems like multiobjective, noncontinuous NSO, inexact data and nonsmooth equations. Part IV of the book focuses on derivative free methods including discrete gradient based methods, model based approaches and other derivative free methods. Finally, Part V deals with constraints like penalty functions, linearization and filter method. Throughout the book assembles applications from image denoising, optimal control, neural network training and many more. weiterlesen