A controlled migration genetic algorithm operator for hardware-in-the-loop experimentation

作     者：Gladwin, D. Stewart, P. Stewart, J. 

作者机构：Lincoln Univ Sch Engn Lincoln LN6 7TS England Univ Sheffield Dept Elect & Elect Engn Sheffield S1 3JD S Yorkshire England 

出 版 物：《ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE》 (人工智能的工程应用)

年 卷 期：2011年第24卷第4期

页      面：586-594页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Genetic algorithms Hardware-in-the-loop Migration Response surfaces Engines 

摘      要：In this paper, we describe the development of an extended migration operator, which combats the negative effects of noise on the effective search capabilities of genetic algorithms. The research is motivated by the need to minimise the number of evaluations during hardware-in-the-loop experimentation, which can carry a significant cost penalty in terms of time or financial expense. The authors build on previous research, where convergence for search methods such as simulated annealing and variable neighbourhood search was accelerated by the implementation of an adaptive decision support operator. This methodology was found to be effective in searching noisy data surfaces. Providing that noise is not too significant, genetic algorithms can prove even more effective guiding experimentation. It will be shown that with the introduction of a controlled migration operator into the GA heuristic, data, which represents a significant signal-to-noise ratio, can be searched with significant beneficial effects on the efficiency of hardware-in-the-loop experimentation, without a priori parameter tuning. The method is tested on an engine-in-the-loop experimental example, and shown to bring significant performance benefits. (C) 2011 Elsevier Ltd. All rights reserved.