Abstract
This work presents a class of smooth modifications of space-filling curves applied to global optimization problems. These modifications make the approximations of the Peano curves (evolvents) differentiable in all points, and save the differentiability of the optimized function. To evaluate the proposed approach, some results of numerical experiments with the original and modified evolvents for solving global optimization problems are discussed.
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Acknowledgements
This research was supported by the Russian Science Foundation, project No 16-11-10150 Novel efficient methods and software tools for time-consuming decision-making problems using supercomputers of superior performance.
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Goryachih, A. (2017). A Class of Smooth Modification of Space-Filling Curves for Global Optimization Problems . In: Kalyagin, V., Nikolaev, A., Pardalos, P., Prokopyev, O. (eds) Models, Algorithms, and Technologies for Network Analysis. NET 2016. Springer Proceedings in Mathematics & Statistics, vol 197. Springer, Cham. https://doi.org/10.1007/978-3-319-56829-4_5
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DOI: https://doi.org/10.1007/978-3-319-56829-4_5
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