Abstract
The global optimization software was developed considering the results of international ”competition” of different algorithms of global optimization (see [30]). Some experience in real life optimization problems was also used selecting the set of optimization algorithms. The set of algorithms of global optimization includes
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four versions of the Bayesian search,
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a version of clustering, a version of uniform deterministic grid,
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a version of pure Monte Carlo search.
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© 1997 Springer Science+Business Media Dordrecht
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Mockus, J., Eddy, W., Mockus, A., Mockus, L., Reklaitis, G. (1997). Introduction to Global Optimization Software (GM). In: Bayesian Heuristic Approach to Discrete and Global Optimization. Nonconvex Optimization and Its Applications, vol 17. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2627-5_17
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DOI: https://doi.org/10.1007/978-1-4757-2627-5_17
Publisher Name: Springer, Boston, MA
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