Abstract
Multifidelity global optimization methods have the potential to allow the optimization of problems which are computationally expensive and have high dimensionality. The DIRECT algorithm has been modified to incorporate multifidelity information. Two correction strategies have been employed with problems with up to ten dimensions and thousands of local optima. DIRECT has demonstrated the ability to reach the same global optimum using high fidelity analyses or corrected low fidelity function values. Initial work with two correction strategies have shown a minor reduction in the number of high-fidelity analyses required but refinements to the stopping criteria have the potential for greatly reducing the cost of the optimization.
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Cox, S.E., Haftka, R.T. (2003). Multifidelity Global Optimization Using DIRECT. In: Biegler, L.T., Heinkenschloss, M., Ghattas, O., van Bloemen Waanders, B. (eds) Large-Scale PDE-Constrained Optimization. Lecture Notes in Computational Science and Engineering, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55508-4_5
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DOI: https://doi.org/10.1007/978-3-642-55508-4_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-05045-2
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