| 书目名称 | Evolutionary Optimization: the µGP toolkit | | 编辑 | Ernesto Sanchez,Massimiliano Schillaci,Giovanni Sq | | 视频video | | | 概述 | Describes an award-winning evolutionary algorithm used for solving practical problems in industry.Provides a practical guide on using the µGP, a set of examples to clarify the available choices and ad | | 图书封面 |  | | 描述 | .This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled μGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers..For a practitioner, μGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results..For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested..MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/. | | 出版日期 | Book 2011 | | 关键词 | Evolutionary Optimization; Genetic Programming; Graph-based representation; Industrial Problems; MicroGP | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-09426-7 | | isbn_softcover | 978-1-4899-9368-7 | | isbn_ebook | 978-0-387-09426-7 | | copyright | Springer Science+Business Media, LLC 2011 |
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发表于 2025-3-21 17:06:32
