| Article ID: | iaor20032537 |
| Country: | Germany |
| Volume: | 93 |
| Issue: | 2 |
| Start Page Number: | 217 |
| End Page Number: | 225 |
| Publication Date: | Jan 2002 |
| Journal: | Mathematical Programming |
| Authors: | Ye Y., Tseng P. |
| Keywords: | programming: linear |
Recently, interior-point algorithms have been applied to nonlinear and nonconvex optimization. Most of these algorithms are either primal–dual path-following or affine-scaling in nature, and some of them are conjectured to converge to a local minimum. We give several examples to show that this may be untrue and we suggest some strategies for overcoming this difficulty.