Localized probability of improvement for kriging based multi-objective optimization

Open Physics

Barba Paolo Di¹  Sykulski Jan K.²  Xiao Song²  Li Yinjiang²  Rotaru Mihai² 

[1] Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy;Electronics and Computer Science, University of Southampton, SouthamptonSO17 1BJ, United Kingdom of Great Britain and Northern Ireland;

关键词: kriging;    multi-objective optimization;    pareto front;    surrogate-based optimization;    89.20.kk;    85.85.+j;    85.70.-w;    87.10.mn;   

DOI  :  10.1515/phys-2017-0117

来源: DOAJ

【 摘 要 】

The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.

【 授权许可】

Unknown