Evolutionary optimization of expensive multiobjective problems with co-sub-Pareto front Gaussian process surrogates

• Main Authors: Luo, Jianping, Gupta, Abhishek, Ong, Yew-Soon, Wang, Zhenkun
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Computer science and engineering; Expensive Optimization; Multiobjective Evolutionary Algorithm (EA)
• Online Access: https://hdl.handle.net/10356/150433
• Institution: Nanyang Technological University

This paper proposes a Gaussian process (GP) based co-sub-Pareto front surrogate augmentation strategy for evolutionary optimization of computationally expensive multiobjective problems. In the proposed algorithm, a multiobjective problem is decomposed into a number of subproblems, the solution of ea...