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
Appears in Collections:Conferences Paper