Self-adaptive Lower Confidence Bound: A New General and Effective Prescreening Method for Gaussian Process Surrogate Model Assisted Evolutionary Algorithms KU Leuven
Surrogate model assisted evolutionary algorithms are receiving much attention for the solution of optimization problems with computationally expensive function evaluations. For small scale problems, the use of a Gaussian Process surrogate model and prescreening methods has proven to be effective. However, each commonly used prescreening method is only suitable for some types of problems, and the proper prescreening method for an unknown problem ...