Abstract
The efficient global optimization (EGO) algorithm based on the Kriging surrogate model is popular. One of the main problems is to determine the infill sampling criteria. An adaptive distance function is proposed and applied to the EI, PI, and MP criteria. The criteria base on a fix distance is also investigated. Seven test problems were used to evaluate these criteria. The results show that the MMP criterion has poor global search ability. PEI, KB and DMP criteria perform better and have better convergence speed and stability.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.