Abstract
This chapter is devoted to algorithms for solving nonsmooth unconstrained difference of convex optimization problems. Different types of stationarity conditions are discussed and the relationship between sets of different stationary points (critical, Clarke stationary and inf-stationary) is established. Bundle methods are developed based on a nonconvex piecewise linear model of the objective function and the convergence of these methods is studied. Numerical results are presented to demonstrate the performance of the methods.
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Acknowledgements
This work was financially supported by the University of Turku, the Academy of Finland (Projects 294002 and 319274) and the Australian Government through the Australian Research Council’s Discovery funding scheme (Project No. DP190100580).
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Joki, K., Bagirov, A.M. (2020). Bundle Methods for Nonsmooth DC Optimization. In: Bagirov, A., Gaudioso, M., Karmitsa, N., Mäkelä, M., Taheri, S. (eds) Numerical Nonsmooth Optimization. Springer, Cham. https://doi.org/10.1007/978-3-030-34910-3_8
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