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Can I read Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications (Nonconvex Optimization and Its Applications (17)) on EtoBox?

Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications (Nonconvex Optimization and Its Applications (17)) by Jonas Mockus, William Eddy, Audris Mockus, Linas Mockus, Gintaras Reklaitis (auth.) is a nonfiction available to read on EtoBox.

What is Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications (Nonconvex Optimization and Its Applications (17)) about?

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. The developed framework is applied in forecasting, in neural network optimization, and in a large number of discrete and continuous optimization problems. Specific application areas which are discussed include scheduling and visualization problems in chemical engineering, manufacturing process control, and epidemiology. Computational results and comparisons with a broad range of test examples are presented. The software required for implementation of the Bayesian Heuristic Approach is included. Although some knowledge of mathematical statistics is necessary in order

Who reads Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications (Nonconvex Optimization and Its Applications (17))?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Jonas Mockus, William Eddy, Audris Mockus, Linas Mockus, Gintaras Reklaitis (auth.)
Publisher
Springer US : Imprint : Springer
Published
1997
Language
EN
ISBN
9780792343271
Category
nonfiction
Subjects
Mathematics, Engineering, Computer Science

Other editions & translations

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