Combining global and local surrogate models to accelerate evolutionary optimization

• المؤلفون الرئيسيون: Zhou, Zongzhao, Ong, Yew-Soon, Nair, Prasanth B., Keane, Andy J., Lum, Kai Yew
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2021
• الموضوعات: Engineering::Computer science and engineering; Aerodynamic Shape Design; Evolutionary Optimization
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/147970
• المؤسسة: Nanyang Technological University

In this paper, we present a novel surrogate-assisted evolutionary optimization framework for solving computationally expensive problems. The proposed framework uses computationally cheap hierarchical surrogate models constructed through online learning to replace the exact computationally expensive...