GA解决多参数超大解空间优化问题的启发式搜索方法

英文篇名：THE HEURISTIC SEARCHING METHODS ON SOLVING OPTIMAL PROBLEM OF MULTI-PARAMETER AND HUGE SOLUTION USING GA
中文刊名：物探化探计算技术
英文刊名：Computing Techniques for Geophysical and Geochemical Exploration
作者：王玉兰 ; 沈越江 ; 杨绍国
英文作者：WANG Yu-lan~1 ; SHEN Yue-jiang~2 ; YANG Shao-guo~1 (1.Institute of MG in CDUT ; Chengdu 610059 ; China ; 2.Institute of Southwest Company of SINAPEC ; Chengdu 610081 ; China ).
中文关键词：遗传算法 ; 多参数解空间 ; 启发式搜索 ; 地震波反演
英文关键词：genetic algorithm ; multi-parameters space ; heuristic searching methods ; seismic data inversion
出版日期：2005-05-28
机构：成都理工大学数学地质研究所,西南石油地质局研究院,成都理工大学数学地质研究所成都610059 ,成都610081 ,成都610059
年：2005
期：02
出版单位：物探化探计算技术

摘要

遗传算法(GA)作为一种有效的全局寻优算法,由于其计算原理简单、搜索能力强、对搜索空间要求低等特点,在许多优化问题中得到了广泛地应用。这里讨论了遗传算法(GA)对多参数超大解空间优化问题的求解方法,重点探讨了提高GA搜索速度的方法,给出了几种启发式搜索策略,并应用于地震波反演这个典型的多参数超大解空间优化问题中,有效地提高了GA的搜索能力,加快了收敛速度。
For the easy understanding in principles and few requirement for searching space, genetic algorithm (GA), as a searching optimal solution algorithm in whole solution space, has been widely applied to many fields. In this paper, we discuss the algorithm of GA in multi-parameter and huge solution space with emphasizing on the improvement of the searching speed of GA. Some heuristic searching methods have been studied and illustrated with a seismic data inversion, which is a typical problem of multi-parameter and huge solution space. The result shows that the searching speed is improved greatly.

引文

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