This page concerns a Matlab implementation of a space mapping toolbox. The toolbox contains implementations of 6 optimization algorithms, based on the space mapping technique, and 5 test problems.
The problems to be solved by the optimization algorithms in this toolbox have two models available: One model denoted the fine model, being the model of primary interest, and the other denoted the coarse model. The fine model is often expensive to evaluate, though this is not always the case with the simple test problems in this toolbox. It is expected that the coarse model somehow resembles the behaviour of the fine model. Further, it is expected that the coarse model is cheaper to evaluate than the fine model, and therefore it is most likely less accurate than the fine model.
The space mapping optimization algorithms employ the coarse model in the search for the fine model minimizer. This in done through a parameter mapping, the so-called space mapping, which in effect makes the coarse model behave as the fine model.
We call this combination of the space mapping and the coarse model, the mapped coarse model. Hence, in the space mapping technique, this mapped coarse model is to take the place of the fine model in search for a minimizer of the latter.
The toolbox is available as the ZIP archive spacemap.zip (430 kb).
Download a manual to the toolbox in PS format (1.4 mb) or PDF format (0.4 mb).
The PhD thesis of Jacob Søndergaard, "Optimization using surrogate models - by the space mapping technique" (2003) describes aspects of space mapping theory.
The master project of Pernille Brock "Optimization Using Space Mapping" (2004) describes the extensions made in 2004.
Please note that the use of the software and the manual is subject to these license terms.
The toolbox and documentation was written by Jacob Søndergaard and Pernille Brock.
Please direct communication to Kaj Madsen.