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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© 1992 Springer Science+Business Media Dordrecht
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Haftka, R.T., Gürdal, Z. (1992). Decomposition and Multilevel Optimization. In: Elements of Structural Optimization. Solid Mechanics And Its Applications, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-2550-5_10
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DOI: https://doi.org/10.1007/978-94-011-2550-5_10
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