基于網格法的遺傳算法及其應用

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基于網格法的遺傳算法及其應用

高玉根, 王國彪, 丁予展

文章導航 > 工程科學學報 > 2002 > 24(3): 360-363

高玉根, 王國彪, 丁予展. 基于網格法的遺傳算法及其應用[J]. 工程科學學報, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

引用本文:

高玉根, 王國彪, 丁予展. 基于網格法的遺傳算法及其應用[J]. 工程科學學報, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

GAO Yugen, WANG Guobiao, DING Yuzhan. Genetic Algorithms Based on Grid and Its Application[J]. Chinese Journal of Engineering, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

Citation:

GAO Yugen, WANG Guobiao, DING Yuzhan. Genetic Algorithms Based on Grid and Its Application[J]. Chinese Journal of Engineering, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

高玉根, 王國彪, 丁予展. 基于網格法的遺傳算法及其應用[J]. 工程科學學報, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

引用本文:

高玉根, 王國彪, 丁予展. 基于網格法的遺傳算法及其應用[J]. 工程科學學報, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

GAO Yugen, WANG Guobiao, DING Yuzhan. Genetic Algorithms Based on Grid and Its Application[J]. Chinese Journal of Engineering, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

Citation:

GAO Yugen, WANG Guobiao, DING Yuzhan. Genetic Algorithms Based on Grid and Its Application[J]. Chinese Journal of Engineering, 2002, 24(3): 360-363. doi: 10.13374/j.issn1001-053x.2002.03.077

基于網格法的遺傳算法及其應用

doi: 10.13374/j.issn1001-053x.2002.03.077

1. 北京科技大學土木與環境工程學院, 北京 100083;
2. 山東工程學院, 淄博 255012

基金項目:

國家自然科學基金資助課題(No.59705010)

作者簡介:
高玉根男,37歲,副教授,博士

中圖分類號: TP301.6
計量
- 文章訪問數: 159
- HTML全文瀏覽量: 25
- PDF下載量: 8
- 被引次數: 0
出版歷程
- 收稿日期: 2001-05-11
- 網絡出版日期: 2021-08-21

Genetic Algorithms Based on Grid and Its Application

1. Civil and Environment Engineering School, UST Beijing, Beijing 100083, China;
2. Shandong Institute of Technology, Zibo 255012, China

摘要: 在基本的遺傳算法(SGA)中,初始群體是隨機產生的.為了增加個體的遍歷性和多樣性提出一種用網格法來產生遺傳算法的初始群體,并對網格法的遺傳算法的優化效率進行了定量的評價.同時與基本的遺傳算法一起應用在DeJong的測試函數F1上便于進行對比.評價結果和實驗結果表明網格法在提高遺傳算法的優化效率上是可行的.
- 遺傳算法 /
- 網格法 /
- 優化算法
Abstract: In Simple Genetic Algorithms(SGA), chromosomes are produced at random. In order to increase the popularity and diversity of individuals, a new genetic algorithms which produces chromosomes with grid is proposed, and its optimization efficiency is evaluated quantitatively. For comparision with SGA, the DeJong Function Flis used an example.Both results show that the new genetic algorithms with grid is valid for improving the optimal efficiency of genetic algorithms.
- genetic algorithms /
- grid /
- optimization algorithm

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文章訪問數: 159
HTML全文瀏覽量: 25
PDF下載量: 8
被引次數: 0

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