.png){kind=icon}
.png){kind=icon}
Return
Efficient Bayesian optimization for cheap and expensive multi-objective problems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.apm.2025.116501.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Hypervolume-based expected improvement matrix infill criterion is developed for optimizing cheap and expensive multi-objective problems • Two-stage dynamic reference point setting strategy is proposed to reasonably balance global and local optimization • Local upper bound points are introduced to further improve optimization accuracy • Experimental results demonstrate the high efficiency of the proposed method
Journal
IF:
5.1
Papers:
1.1K
Citations:
2.8W