%0 Conference Paper %1 Chen06adaptivediscretization %A hong Chen, Chao %A hong Chen, Chao %A nan Liu, Wei %A nan Liu, Wei %A ping Chen, Ying %A ping Chen, Ying %B In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2006 %D 2006 %K imported %P 1103--1110 %T Adaptive discretization for probabilistic model building genetic algorithms %X 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. 1

@inproceedings{Chen06adaptivediscretization, abstract = {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. 1}, added-at = {2009-04-13T23:55:58.000+0200}, author = {hong Chen, Chao and hong Chen, Chao and nan Liu, Wei and nan Liu, Wei and ping Chen, Ying and ping Chen, Ying}, biburl = {https://www.bibsonomy.org/bibtex/2de270b173f7417a7cd0d6ea9ff8143ca/dalbem}, booktitle = {In Proceedings of ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO-2006}, description = {Adaptive discretization for probabilistic model building genetic algorithms}, interhash = {da04af26875481e57ae627284413d8dc}, intrahash = {de270b173f7417a7cd0d6ea9ff8143ca}, keywords = {imported}, pages = {1103--1110}, timestamp = {2009-04-13T23:55:58.000+0200}, title = {Adaptive discretization for probabilistic model building genetic algorithms}, year = 2006 }