Abstract
The paper addresses the problem of constructing lower and upper bounding functions for univariate functions. This problem is of a crucial importance in global optimization where such bounds are used by deterministic methods to reduce the search area. It should be noted that bounding functions are expected to be relatively easy to construct and manipulate with. We propose to use piecewise linear estimators for bounding univariate functions. The rules proposed in the paper enable an automated synthesis of lower and upper bounds from the function’s expression in an algebraic form. Numerical examples presented in the paper demonstrate the high accuracy of the proposed bounds.
The reported study was funded by RFBR according to the research project 17-07-00510.
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Khamisov, O., Posypkin, M., Usov, A. (2019). Piecewise Linear Bounding Functions for Univariate Global Optimization. In: Evtushenko, Y., Jaćimović, M., Khachay, M., Kochetov, Y., Malkova, V., Posypkin, M. (eds) Optimization and Applications. OPTIMA 2018. Communications in Computer and Information Science, vol 974. Springer, Cham. https://doi.org/10.1007/978-3-030-10934-9_13
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DOI: https://doi.org/10.1007/978-3-030-10934-9_13
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