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In the field of multi-objective optimization algorithms, multi-objective Bayesian Global Optimization (MOBGO) is an important branch, in addition to evolutionary multi-objective optimization algorithms. MOBGO utilizes Gaussian Process models learned from previous objective function evaluations to decide the next evaluation site by maximizing or minimizing an infill criterion. A commonly used criterion...
Over the past decades, evolutionary multi-objective optimization algorithms have shown their strength on solving the multi-objective optimization problems. The S-Metric Selection Evolutionary Multiobjective Optimization Algorithm (SMS-EMOA) is a state-of-the-art algorithm which uses the hypervolume indicator as selection criterion and performs well in finding well distributed solutions to approximate...
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