Bayesian Optimization for Multi-objective Optimization and Multi-point Search

Understand

Bayesian optimization is an effective method to efficiently optimize unknown objective functions with high evaluation costs.

• Traditional Bayesian optimization algorithms select one point per iteration for single objective function, whereas in recent years, Bayesian optimization for multi-objective optimization or multi-point search per iteration have been proposed.
• However, Bayesian optimization that can deal with them at the same time in non-heuristic way is not known at present.
• We propose a Bayesian optimization algorithm that can deal with multi-objective optimization and multi-point search at the same time.