Global Optimization From Theory to Implementation

Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems, especially those of large scale for which exact optimization approaches can be prohibitively costly. The book covers all aspects ranging from the formal presentation of the Bayesian Approach, to its extension to the Bayesian Heuristic Strategy, and its utilization within the informal, interactive Dynamic Visualization strategy.

Authors: Tuy, Hoang
Presents up-to-date research and methodologies in modern global optimization
Serves as a reference for a wide swath of the optimization community
Equips readers to handle a mathematically rigorous approach to modern global optimization and its potential applications
Covers fundamental concepts, theoretical foundations and practical implementation of algorithms