A set of examples of global and discrete optimization. Applications of Bayesian heuristic approach
The book presents Bayesian heuristic approach as a tool to improve heuristic solutions for several well known optimization problems. It is intended to be a tool to be used as material in a operations research course together with software available in the related Internet sites (\url{http://mockus.org/optimum} and others). After a short theoretical introduction, most of the book is dedicated to examples and software description. A Global Minnimizer is presented which includes Bayesian search, clustering, and Monte Carlo search, together with three local optimization methods (two clasical ones and one proposed by the author). Part III of the book presents examples of application of the software at several problems. Theoretical background in optimization methods and other subjects treated is required to read the book. Part of the material in the mentioned site is in Lithuanian.
scientific article; zbMATH DE number 1506310