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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/28859
Title: Introduction to the space mapping
Authors: Bandler, John
Madsen, Kaj
Keywords: space mapping;surrogate modeling;coarse models;fine models;parameter extraction;convergence;archery example
Publication Date: 18-May-2005
Citation: Bandler, John and K. Madsen, “Introduction to the space mapping,” SIAM Conference on Optimization, Stockholm, Sweden, May 18, 2005.
Abstract: The Space Mapping technique is intended for optimization of engineering models which involve very expensive function evaluations. We use two different models of the same physical system: Besides the CPU-intensive model of primary interest (denoted the fine model), access to a less expensive (coarse) model is assumed which may be less accurate. The main idea of the Space Mapping technique is to use the coarse model to gain information about the fine model, and to apply this in the search for an optimal solution of the latter. Thus the technique iteratively establishes a mapping between the parameters of the two models which relate similar model responses. Having this mapping, most of the model evaluations can be directed to the fast coarse model. In this talk the idea behind the method is presented. Mathematical descriptions and motivations are given, and two examples are presented as illustrations. Conditions for convergence of Space Mapping methods are discussed.
Description: Slides for a presentation given as part of the “Space mapping: a knowledge-based engineering modeling and optimization methodology exploiting surrogates” session co-organized by Bandler and Madsen at the Eighth SIAM Conference on Optimization. The conference was held May 15 through 19, 2005 in Stockholm, Sweden.
URI: http://hdl.handle.net/11375/28859
Appears in Collections:John Bandler Slides

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