Special Issue On Optimization And Optimal Control With Applications For The 4th International Conference On Optimization And Control With Applications Oca2009 June 6 11 2009 Harbin China

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Entropy Optimization and Mathematical Programming

Entropy Optimization and Mathematical Programming
Author :
Publisher : Springer Science & Business Media
Total Pages : 350
Release :
ISBN-10 : 9781461561316
ISBN-13 : 1461561310
Rating : 4/5 (310 Downloads)

Book Synopsis Entropy Optimization and Mathematical Programming by : Shu-Cherng Fang

Download or read book Entropy Optimization and Mathematical Programming written by Shu-Cherng Fang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.


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