Pseudo expected improvement criterion for parallel EGO algorithm

• Published in: Journal of global optimization Vol. 68; no. 3; pp. 641 - 662
• Main Authors: Zhan, Dawei, Qian, Jiachang, Cheng, Yuansheng
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2017; Springer; Springer Nature B.V
• Subjects: Algorithms; Benchmarks; Computer Science; Computer simulation; Computing time; Convergence; Criteria; Design analysis; Efficiency; Global optimization; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Parallel processing; Real Functions; State of the art; Expected improvement; Parallel computing; Influence function; Efficient global optimization; Pseudo expected improvement

The efficient global optimization (EGO) algorithm is famous for its high efficiency in solving computationally expensive optimization problems. However, the expected improvement (EI) criterion used for picking up candidate points in the EGO process produces only one design point per optimization cyc...