Abstract
A new approach to the global optimization of functions with extremely rugged graphs is introduced. This multilevel search method is both an algorithm and a meta-algorithm, a logic for regulating optimization done by other algorithms. First, it is examined in the one-dimensional case theoretically and through simple examples. Then, to deal with higher dimensions, multilevel search is combined with the Monte Carlo method; this hybrid algorithm is tested on standard problems and is found to perform extremely well for a derivative-free method.
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Communicated by L. C. W. Dixon
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Goertzel, B. Global optimization by multilevel search. J Optim Theory Appl 75, 423–432 (1992). https://doi.org/10.1007/BF00941477
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DOI: https://doi.org/10.1007/BF00941477