Abstract
In this article, a generalization of the ECP algorithm to cover a class of nondifferentiable Mixed-Integer NonLinear Programming problems is studied. In the generalization constraint functions are required to be -pseudoconvex instead of pseudoconvex functions. This enables the functions to be nonsmooth. The objective function is first assumed to be linear but also -pseudoconvex case is considered. Furthermore, the gradients used in the ECP algorithm are replaced by the subgradients of Clarke subdifferential. With some additional assumptions, the resulting algorithm shall be proven to converge to a global minimum.
| Original language | Undefined/Unknown |
|---|---|
| Pages (from-to) | 641–661 |
| Number of pages | 21 |
| Journal | Optimization |
| Volume | 64 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2015 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- alpha ECP
- extended cutting plane algorithm
- generalized convexity
- mixed-integer programming
- nonsmooth MINLP
- nonsmooth optimization
- pseudoconvex function
- subgradient