Abstract: This article proposes a novel constrained multiobjective evolutionary Bayesian optimization algorithm based on decomposition (named CMOEBO/D) for expensive constrained multiobjective ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

Abstract: Parallel Bayesian optimization is crucial for solving expensive black-box problems, yet batch acquisition strategies remain a challenge. To address this, we propose a novel parallel ...

% Q. Zhang, W. Liu, E. Tsang, and B. Virginas. Expensive Multiobjective % Optimization by MOEA/D with Gaussian Process model. IEEE Transactions on % Evolutionary ...

ABSTRACT: The rapid proliferation of the Internet of Things (IoT) and Industrial IoT (IIoT) has revolutionized industries through enhanced connectivity and automation. However, this expansion has ...

The growing demand for innovative research in the food industry is driving the adoption of robots in large-scale experimentation, a shift that offers increased precision, repeatability, and efficiency ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

Electromagnetic brain imaging is the reconstruction of brain activity from non-invasive recordings of electroencephalography (EEG), magnetoencephalography (MEG), and also from invasive ones such as ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...