The hypervolume metric is widely used to guide the search in multiobjective optimization.
However, in parallel expensive multiobjective optimization, the hypervolume-based …

Aerospace product design optimizations, such as micro-aerial vehicle fuselage design, often
involve multiple objectives. Multi-objective Bayesian optimization (MOBO) is an efficient …

Parallel infill sampling is a promising approach to improve the efficiency of multi-fidelity multi-
objective Bayesian optimization (MOBO). In existing literature, the number of infill samples …

In this paper, a multi-fidelity Bayesian optimization approach is presented to tackle
computationally expensive constrained multiobjective optimization problems (MOPs). The …

Multipoint infill sampling has emerged recently as a promising tool to enhance the efficiency
of the adaptive Kriging-based optimization method for computational expensive …

In solving expensive multi-objective optimization problems, surrogate models have been
widely investigated. The existing multi-objective algorithms adopting surrogate models can …

With advancements in computer technology, Computational fluid dynamics (CFD) theory
provides a numerical tool for evaluating the comprehensive hydrodynamic performance of …

The profile and axial designs of a volute tongue have great influences on the internal flow
conditions and aerodynamic performance of a forward-curved blade centrifugal fan. In order …

To reduce optimization time spent on real-world expensive multi-objective optimization
problems (MOPs), a relatively large number of points added in each cycle is an effective way …

The main goal of this paper is to show that Bayesian optimization can be regarded as a
general framework for the data-driven modelling and solution of problems arising in water …