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Computational Intelligence in Optimization
. Ed(S): Tenne, Yoel; Goh, Chi-Keong
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Description for Computational Intelligence in Optimization
Hardback. This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more. Editor(s): Tenne, Yoel; Goh, Chi-Keong. Series: Adaptation, Learning, and Optimization. Num Pages: 412 pages, 74 colour illustrations, biography. BIC Classification: PBW; TBC; TJFM1; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 25. Weight in Grams: 885.
Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools. With the increasing challenges of ful?lling optimization goals of current applications there is a strong drive to advancethe developmentofe?cientoptimizers. The challengesintroduced by emerging problems include: * objective functions which are prohibitively expensive to evaluate, so ty- callysoonlyasmallnumber ofobjectivefunctionevaluationscanbemade during the entire search, * objective functions which are highly multimodal or discontinuous, and * non-stationary problems which may change in time (dynamic). Classical optimizers may perform poorly or even may fail to produce any improvement over ... Read more
Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools. With the increasing challenges of ful?lling optimization goals of current applications there is a strong drive to advancethe developmentofe?cientoptimizers. The challengesintroduced by emerging problems include: * objective functions which are prohibitively expensive to evaluate, so ty- callysoonlyasmallnumber ofobjectivefunctionevaluationscanbemade during the entire search, * objective functions which are highly multimodal or discontinuous, and * non-stationary problems which may change in time (dynamic). Classical optimizers may perform poorly or even may fail to produce any improvement over ... Read more
Product Details
Format
Hardback
Publication date
2010
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
412
Condition
New
Series
Adaptation, Learning, and Optimization
Number of Pages
412
Place of Publication
Berlin, Germany
ISBN
9783642127748
SKU
V9783642127748
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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