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...
Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This b...
This book shows how the Bayesian Approach (BA) improves well- known heuristics by randomizing and optimizing their parameters. That is the Bayesian Heuristic Approach (BHA). The ten in-depth examples are designed to teach Operations Research using Internet. Each example is a simple representation of some impor- tant family of real-life problems. The accompanying software can be run by remote Internet users. The supporting web-sites include software for Java, C++, and other lan- guages. A theoretical setting is described in which one can discuss a Bayesian adaptive choice of heuristics for...
This book shows how the Bayesian Approach (BA) improves well- known heuristics by randomizing and optimizing their parameters. That is the Bayesian He...
