Abstract
We construct exact. D-efficient designs for linear regression models using a hybrid algorithm that consists of genetic and local search components. The genetic component is a genetic algorithm (GA) with a 100% mutation rate and ranking selection. The local search methods we use are based on the G-bit improvement and a combination of the Powel multidimensional and Brent line optimization techniques. Computational results show that the hybrid algorithm generates designs that are comparable in efficiency to those found using the modified Fedorov algorithm (MFA), but without being limited to using a given set of candidate points.
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Ali, A.A., Jansson, M. (2004). Hybrid Algorithms for Construction of D-Efficient Designs. In: Antoch, J. (eds) COMPSTAT 2004 — Proceedings in Computational Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2656-2_2
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DOI: https://doi.org/10.1007/978-3-7908-2656-2_2
Publisher Name: Physica, Heidelberg
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