| 书目名称 | Multimodal Optimization by Means of Evolutionary Algorithms | | 编辑 | Mike Preuss | | 视频video | | | 概述 | Describes state of the art in algorithms, measures and test problems.Approaches multimodal optimization algorithms via model-based simulation and statistics.Valuable for practitioners with real-world | | 丛书名称 | Natural Computing Series | | 图书封面 |  | | 描述 | .This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. ..The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used...The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.. | | 出版日期 | Book 2015 | | 关键词 | Evolutionary algorithms; Evolutionary computing; Experimental analysis; Multimodal optimization; Niching | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-07407-8 | | isbn_softcover | 978-3-319-79156-2 | | isbn_ebook | 978-3-319-07407-8Series ISSN 1619-7127 Series E-ISSN 2627-6461 | | issn_series | 1619-7127 | | copyright | Springer International Publishing Switzerland 2015 |
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发表于 2025-3-21 16:20:53
