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Titlebook: OmeGA; A Competent Genetic Dimitri Knjazew Book 2002 Springer Science+Business Media New York 2002 Industrie.algorithms.calculus.code.comb

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樓主
發(fā)表于 2025-3-21 16:16:33 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱OmeGA
副標(biāo)題A Competent Genetic
編輯Dimitri Knjazew
視頻videohttp://file.papertrans.cn/701/700887/700887.mp4
叢書名稱Genetic Algorithms and Evolutionary Computation
圖書封面Titlebook: OmeGA; A Competent Genetic  Dimitri Knjazew Book 2002 Springer Science+Business Media New York 2002 Industrie.algorithms.calculus.code.comb
描述.OmeGA: A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems. addresses two increasingly important areas in GA implementation and practice. OmeGA, or the ordering messy genetic algorithm, combines some of the latest in competent GA technology to solve scheduling and other permutation problems. Competent GAs are those designed for principled solutions of hard problems, quickly, reliably, and accurately. Permutation and scheduling problems are difficult combinatorial optimization problems with commercial import across a variety of industries. ..This book approaches both subjects systematically and clearly. The first part of the book presents the clearest description of messy GAs written to date along with an innovative adaptation of the method to ordering problems. The second part of the book investigates the algorithm on boundedly difficult test functions, showing principled scale up as problems become harder and longer. Finally, the book applies the algorithm to a test function drawn from the literature of scheduling. .
出版日期Book 2002
關(guān)鍵詞Industrie; algorithms; calculus; code; combinatorial optimization; design; development; genetic algorithms;
版次1
doihttps://doi.org/10.1007/978-1-4615-0807-6
isbn_softcover978-1-4613-5249-5
isbn_ebook978-1-4615-0807-6Series ISSN 1568-2587
issn_series 1568-2587
copyrightSpringer Science+Business Media New York 2002
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沙發(fā)
發(fā)表于 2025-3-21 20:20:06 | 只看該作者
板凳
發(fā)表于 2025-3-22 04:10:27 | 只看該作者
Development of the Ordering Messy Genetic Algorithm,rs of real numbers—the so-called.introduced by Bean (1994). In a number of experiments it is shown that the OmeGA significantly outperforms the simple GA in solving ordering deceptive problems, which are hard sequencing problems defined elsewhere (Kargupta et al., 1992).
地板
發(fā)表于 2025-3-22 06:02:32 | 只看該作者
Performance Analysis of the Omega,problems were composed of eight order-four deceptive subfunctions. The OmeGA outperformed the random key-based simple GA for problems with loosely coded building blocks. However, the experiments were conducted with non-overlapping BBs of equal size and scale, that is, with uniform contribution to the fitness function.
5#
發(fā)表于 2025-3-22 09:23:44 | 只看該作者
Application to a Scheduling Problem,the second chapter, it is hard or even impossible to estimate the building-block structure of real-world problems. We do not know the number, the size, or the scale of the BBs. It is also unclear whether they overlap or not.
6#
發(fā)表于 2025-3-22 13:28:14 | 只看該作者
Conclusions and Future Work,In this book we have developed the ordering messy genetic algorithm and have successfully tested its performance in pilot experiments with ordering deceptive problems. By using an adaptive representation scheme, it becomes relatively independent from the underlying problem coding and outperforms the simple GA.
7#
發(fā)表于 2025-3-22 18:50:24 | 只看該作者
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發(fā)表于 2025-3-22 21:20:38 | 只看該作者
OmeGA978-1-4615-0807-6Series ISSN 1568-2587
9#
發(fā)表于 2025-3-23 03:43:54 | 只看該作者
Book 2002 and practice. OmeGA, or the ordering messy genetic algorithm, combines some of the latest in competent GA technology to solve scheduling and other permutation problems. Competent GAs are those designed for principled solutions of hard problems, quickly, reliably, and accurately. Permutation and sch
10#
發(fā)表于 2025-3-23 06:27:50 | 只看該作者
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