Abstract
The hypervolume indicator has been proved as an outstanding metric for the distribution of Pareto points, and the derived hypervolume based expected improvement (HVEI) has received a particular attention in the multi-objective efficient global optimization (EGO) method. However, the high computational cost has become the bottle neck which limits the application of HVEI on many objective optimization. Aiming at this problem, a modified version of HVEI (MHVEI) is proposed in this paper, which is easier to implement, maintains all the desired properties, and has a much lower computational cost. The theoretical study shows that the new criterion can be considered as a weighted integral form of HVEI, and it prefers the new point with a higher uncertainty compared with HVEI. The numerical tests show that the MHVEI performs similar as HVEI on the lower dimensional problem, and the advantage of MHVEI becomes more obvious as the dimension grows.
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.