GP-DEMO: Differential Evolution for Multiobjective Optimization based on Gaussian Process models
New surrogate-model-based evolutionary multiobjective algorithm GP-DEMO is proposed. New relations for comparing solutions under uncertainty are defined. Comparing solutions under uncertainty prevents wrongly performed comparisons. GP-DEMO in comparison to DEMO obtained similar results with less exact evaluations.
gaussian process modeling multiple objective programming evolutionary algorithms surrogate models probable pareto dominance