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＜電子ブック＞
A Set of Examples of Global and Discrete Optimization : Applications of Bayesian Heuristic Approach / by Jonas Mockus
(Applied Optimization ; 41)

版	1st ed. 2000.
出版者	(New York, NY : Springer US : Imprint: Springer)
出版年	2000
本文言語	英語
大きさ	XIV, 322 p : online resource
著者標目	*Mockus, Jonas author SpringerLink (Online service)
件　名	LCSH:Discrete mathematics LCSH:Mathematical optimization LCSH:Statistics  LCSH:Operations research FREE:Discrete Mathematics FREE:Optimization FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Operations Research and Decision Theory
一般注記	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 discrete and global optimization prob­ lems. The techniques are evaluated in the spirit of the average rather than the worst case analysis. In this context, "heuristics" are understood to be an expert opinion defining how to solve a family of problems of dis­ crete or global optimization. The term "Bayesian Heuristic Approach" means that one defines a set of heuristics and fixes some prior distribu­ tion on the results obtained. By applying BHA one is looking for the heuristic that reduces the average deviation from the global optimum. The theoretical discussions serve as an introduction to examples that are the main part of the book. All the examples are interconnected. Dif­ ferent examples illustrate different points of the general subject. How­ ever, one can consider each example separately, too HTTP:URL=https://doi.org/10.1007/978-1-4615-4671-9

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