Abstract
A mathematical programming method particularly suited for structural and multidisciplinary optimization problems is presented. It is based on the idea that all available information about the problem should be used in the attempt to obtain rapid convergence. Thus, it uses information from previous iterations to produce steadily improving approximations of the implicit objective and constraint functions of the problem. In some cases, this creates a response surface type of approximation. The ability of the method to store known information about the behaviour of the problem makes it well-suited for practical multidisciplinary optimization.
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Rasmussen, J. Nonlinear programming by cumulative approximation refinement. Structural Optimization 15, 1–7 (1998). https://doi.org/10.1007/BF01197431
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DOI: https://doi.org/10.1007/BF01197431