標題: | Adaptive discretization for Probabilistic model building genetic algorithms |
作者: | Chen, Chao-Hong Liu, Wei-Nan Chen, Ying-Ping 資訊工程學系 Department of Computer Science |
關鍵字: | adaptive discretization;split-on-demand;extended compact genetic algorithm;real-parameter optimization |
公開日期: | 2006 |
摘要: | This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization problems in the continuous domain. The procedure, effect, and usage of SoD are described in detail. As an example, the integration of SoD and the extended compact genetic algorithm (ECGA), named real-coded ECGA (rECGA), is presented and numerically examined. The experimental results indicate that rECGA works well and SoD is effective. The behavior of SoD is analyzed and discussed, followed by the potential future work for SoD. |
URI: | http://hdl.handle.net/11536/17103 |
ISBN: | 978-1-59593-186-3 |
期刊: | GECCO 2006: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2 |
起始頁: | 1103 |
結束頁: | 1110 |
顯示於類別: | 會議論文 |