Performance Comparison of Evolutionary Algorithms Applied to Hybrid Rocket Problem

被引：0
|
作者：
Chiba, Kazuhisa [1 ]
机构：
[1] Hokkaido Inst Technol, Dept Mech Syst Engn, Sapporo, Hokkaido 0068585, Japan
来源：
6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS | 2012年
关键词：
DIFFERENTIAL EVOLUTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Optimizer is an essence in design-informatics to efficiently obtain nondominated solutions. In the present study, the best optimizer is decided through the competition for the mathematical standard test functions and is also applied to a conceptual design problem of simple single-stage hybrid rocket as the real-world problem. Consequently, a hybrid method between differential evolution and genetic algorithm has good exploration performance. Moreover, the principal component analysis blended crossover and the confidence interval based crossover have good capability on the hybrid method between differential evolution and genetic algorithm.
引用
收藏
页码：1673 / 1678
页数：6
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