Brief description
The SED Toolbox (Sequential Experimental Design) is a powerful Matlab toolbox for the sequential Design of Experiments (DoE). In traditional experimental design, all the design points are selected upfront, before performing any (computer or real-life) experiment, and no additional design points are selected afterwards. This traditional approach is prone to oversampling and/or undersampling because it is often very difficult to estimate the required number of design points in advance. The SED Toolbox solves this problem by providing the user with state-of-the-art algorithms that generate an experimental design sequentially, i.e. one point at a time, without having to provide the total number of design points in advance. This is called sequential experimental design. The SED Toolbox was designed to be extremely fast and easy to use, yet very powerful.
Key features
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Includes several highly efficient space-filling sequential experimental design algorithms, which generate designs competitively with state-of-the-art one-shot experimental design techniques such as Latin hypercubes.
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Optimized for speed: several algorithms are included, ranging from extremely fast, even in high-dimensional problems, to slightly slower (yet still relatively fast).
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All methods support constraints of any kind (linear and nonlinear). These constraints can be specified with a Matlab function.
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Includes the powerful LOLA-Voronoi algorithm, which distributes design points sequentially according to the nonlinearity of the problem, following the assumption that nonlinear regions are more difficult to understand than linear ones.
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Support for rectangular input spaces: not every input is necessarily equally important, so weights can be given to each input and the algorithms will take this into account when selecting design points.
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Easy to use and configure, with examples amply available in the documentation and in the distribution.
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Proper Object Oriented design.
Screenshots
Comparison of SED Toolbox algorithms and other popular sequential and non-sequential experimental design methods:
