This paper examines the influence of two major aspects on the solution quality of surrogate model algorithms for computationally expensive black-box global optimization problems, namely the surrogate model choice and the method of iteratively selecting sample points. A random sampling strategy...

We present the AQUARS (A QUAsi-multistart Response Surface) framework for finding the global minimum of a computationally expensive black-box function subject to bound constraints. In a traditional multistart approach, the local search method is blind to the trajectories of the previous local...

The CIE (International Commission on Illuminance) Standard Skies depicts the typical diffuse luminance and radiance distributions over the skydome. However, it can be challenging to interpret the luminance and radiance distribution into the irradiance and illuminance contributions on tilt planes...

<Para ID="Par1">We consider parameter optimization problems which are subject to constraints given by parametrized partial differential equations. Discretizing this problem may lead to a large-scale optimization problem which can hardly be solved rapidly. In order to accelerate the process of parameter...</para>

This paper deals with the space mapping optimization algorithms in general and with the manifold mapping technique in particular. The idea of such algorithms is to optimize a model with a minimum number of each objective function evaluations using a less accurate but faster model. In this...

The interacting particle system (IPS) is a recent probabilistic model proposed to estimate rare event probabilities for Markov chains. The principle of IPS is to apply alternatively selection and mutation stages to a set of initial particles in order to estimate probabilities or quantiles more...

Determining the optimal rates of groundwater extraction for the sustainable use of coastal aquifers is a complex water resources management problem. It necessitates the application of a 3D simulation model for coupled flow and transport simulation together with an optimization algorithm in a...

Surrogate models are an important part of building energy labelling programs, but these models still present low accuracy, particularly in cooling-dominated climates. The objective of this study was to evaluate the feasibility of using an artificial neural network (ANN) to improve the accuracy...