| 书目名称 | Evolutionary Algorithms and Agricultural Systems | | 编辑 | David G. Mayer | | 视频video | | | 丛书名称 | The Springer International Series in Engineering and Computer Science | | 图书封面 |  | | 描述 | .Evolutionary Algorithms and Agricultural Systems. dealswith the practical application of evolutionary algorithms to the studyand management of agricultural systems. The rationale of systemsresearch methodology is introduced, and examples listed of real-worldapplications. It is the integration of these agricultural systemsmodels with optimization techniques, primarily genetic algorithms,which forms the focus of this book. The advantages are outlined, withexamples of agricultural models ranging from national andindustry-wide studies down to the within-farm scale. The potentialproblems of this approach are also discussed, along with practicalmethods of resolving these problems. .Agricultural applications using alternate optimization techniques(gradient and direct-search methods, simulated annealing andquenching, and the tabu search strategy) are also listed anddiscussed. The particular problems and methodologies of thesealgorithms, including advantageous features that may benefit a hybridapproach or be usefully incorporated into evolutionary algorithms, areoutlined. From consideration of this and the published examples, it isconcluded that evolutionary algorithms are the superior met | | 出版日期 | Book 2002 | | 关键词 | algorithms; evolution; evolutionary algorithm; genetic algorithms; modeling; operations research; optimiza | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4615-1717-7 | | isbn_softcover | 978-1-4613-5693-6 | | isbn_ebook | 978-1-4615-1717-7Series ISSN 0893-3405 | | issn_series | 0893-3405 | | copyright | Springer Science+Business Media New York 2002 |
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发表于 2025-3-21 17:14:30
