Abstract
The resources required for the solution of an optimization problem typically increase with the dimensionality of the problem at a rate which is more than linear. That is, if we double the number of design variables in a problem, the cost of solution will typically more than double. Large problems may also require excessive computer memory allocations. For these reasons we often seek ways of breaking a large optimization problem into a series of smaller problems.
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Haftka, R.T., Gürdal, Z., Kamat, M.P. (1990). Decomposition and Multilevel Optimization. In: Elements of Structural Optimization. Solid Mechanics and Its Applications, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7862-2_10
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DOI: https://doi.org/10.1007/978-94-015-7862-2_10
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