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| Paper IPM / M / 18321 |
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| Abstract: | |
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We develop an algorithm based on the idea of the bundle
trust-region method to solve nonsmooth nonconvex constrained
optimization problems. The resulting algorithm inherits some attractive
features from both bundle and trust-region methods. Moreover,
it allows effective control of the size of trust-region subproblems
via the compression and aggregation techniques of bundle methods.
On the other hand, the trust-region strategy is used to manage
the search region and accept a candidate point as a new successful
iterate. Global convergence of the developed algorithm is studied
under some mild assumptions and its encouraging preliminary
computational results are reported.
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