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Lecture Notes in Computer Science
The aim of this work is to compare different approaches for parallelization in model-based optimization. As another alternative aside from the existing methods, we propose using a multi-objective infill criterion that rewards both the diversity and the expected improvement of the proposed points. This criterion can be applied more universally than the existing ones because it has less requirements. Internally, an evolutionary algorithm is used to optimize this criterion. We verify thedoi:10.1007/978-3-319-09584-4_17 fatcat:jjtkakjd2zeidpf6v4xnvqftyu