Learning to be selective in genetic-algorithm-based design optimization
作者： KHALED RASHEED , HAYM HIRSH
DOI: 10.1017/S0890060499133043
关键词:
摘要: In this paper we describe a method for improving genetic-algorithm-based optimization using search control. The idea is to utilize the sequence of points explored during guide further exploration. proposed particularly suitable continuous spaces with expensive evaluation functions, such as arise in engineering design. Empirical results several design domains demonstrate that can significantly improve efficiency and reliability GA optimizer.
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