Description: Bayesian Heuristic Approach to Discrete and Global Optimization by Jonas Mockus, William Eddy, Gintaras Reklaitis Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. Publisher Description 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 to fathom the theoretical aspects of the development, no specialized mathematical knowledge is required to understand the application of the approach or to utilize the software which is provided. Audience: The book is of interest to both researchers in operations research, systems engineering, and optimization methods, as well as applications specialists concerned with the solution of large scale discrete and/or nonconvex optimization problems in a broad range of engineering and technological fields. It may be used as supplementary material for graduate level courses. Details ISBN 1441947671 ISBN-13 9781441947673 Title Bayesian Heuristic Approach to Discrete and Global Optimization Author Jonas Mockus, William Eddy, Gintaras Reklaitis Format Paperback Year 2010 Pages 397 Edition 1st Publisher Springer-Verlag New York Inc. GE_Item_ID:137953109; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 305.87 USD
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ISBN-13: 9781441947673
Book Title: Bayesian Heuristic Approach to Discrete and Global Optimization
Number of Pages: Xv, 397 Pages
Language: English
Publication Name: Bayesian Heuristic Approach to Discrete and Global Optimization : Algorithms, Visualization, Software, and Applications
Publisher: Springer
Subject: Probability & Statistics / General, Intelligence (Ai) & Semantics, Combinatorics, Optimization, Probability & Statistics / Bayesian Analysis, Discrete Mathematics
Publication Year: 2010
Type: Textbook
Item Weight: 22.4 Oz
Item Length: 9.3 in
Subject Area: Mathematics, Computers
Author: William Eddy, Jonas Mockus, Gintaras Reklaitis
Item Width: 6.1 in
Series: Nonconvex Optimization and Its Applications Ser.
Format: Trade Paperback
