Genetic Algorithms Can Improve the Construction of D-Optimal Experimental Designs
نویسندگان
چکیده
We study the benefits of Genetic Algorithms, in particular the crossover operator, in constructing experimental designs that are D-optimal. To this purpose, we use standard Monte Carlo algorithms such as DETMAX and k-exchange as the mutation operator in a Genetic Algorithm. Compared to the heuristics, our algorithms are slower but yield better results. Key-Words: Genetic Algorithm, Memetic Algorithm, Design of Experiments, DOE, D-Optimal, DETMAX Algorithm, k-Exchange Algorithm, Combinatorial Optimization.
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