Miha Mlakar

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Continuous casting is a widely used steel production process. To yield high-quality steel, the casting parameters have to be tuned with respect to several contradictory criteria. We approached this multiobjective optimization problem in discrete and continuous variants, applying Exhaustive Search (ES) and Differential Evolution for Multiobjective(More)
This paper proposes a novel surrogate-model-based multiobjective evolutionary algorithm called Differential Evolution for Multiobjective Optimization Based on Gaussian Process Models (GP-DEMO). The algorithm is based on the newly defined relations for comparing solutions under uncertainty. These relations minimize the possibility of wrongly performed(More)
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