THE OPTIMIZATION SPEED OF EITIST EVOLUTIONARY ALGORITHMS IN OFF-LINE EHW
The evolvable hardware (EHW) enables the system to be self-adaptive, self-organizing and self-repairing by incorporating evolutionary algorithm (EAs). EHW has a great application potential in weapon equipment system. However,the evolutional speed is slow which impedes its application and development and there lacks theoretical results on optimization speed of evolutionary algorithm in EHW. Mutation has been regarded as one of the key features of EAs.It is important to understand in depth the effect of the mutation operator on evolution speed of EAs. The paper gives some theoretical results by deriving the estimation upper limit of the optimization speed and the mean first hitting time of a given problem. It is shown that estimation upper limit of the optimization speed is completely determined by the transition probability and initial distribution of the population. It is also shown that the m utation probability can have a drastic impact on the optimization speed. For a given problem, the range of mutation probability can be decided quantitatively.
EHW optimization speed mutation elitist evolutionary algorithm
WEI-RONG GUAN HAI-YUN ZHOU BIN SONG
Institute of Applied Mathematics and Mechanics, Ordnance Engineering College, Shijiazhuang 050003, C Department of Equipment Command and Management, Ordnance Engineering College, Shijiazhuang 050003, C
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
2154-2158
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）