Semismooth and Semiconvex Functions in Constrained Optimization

@inproceedings{Mifflin1977SemismoothAS,
  title={Semismooth and Semiconvex Functions in Constrained Optimization},
  author={Robert Mifflin},
  year={1977}
}
We introduce semismooth and semiconvex functions and discuss their properties with respect to nonsmooth nonconvex constrained optimization problems. These functions are locally Lipschitz, and hence have generalized gradients. The author has given an optimization algorithm that uses generalized gradients of the problem functions and converges to stationary points if the functions are semismooth. If the functions are semiconvex and a constraint qualification is satisfied, then we show that a… CONTINUE READING

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