Abstract
This paper considers a method for dealing with non-convex objective functions in optimization problems. It uses the Hessian matrix and combines features of trust-region techniques and continuous steepest descent trajectory-following in order to construct an algorithm which performs curvilinear searches away from the starting point of each iteration. A prototype implementation yields promising results
| Original language | English |
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| Pages (from-to) | 387-407 |
| Journal | Advanced Modeling and Optimization |
| Volume | 15 |
| Issue number | 2 |
| Publication status | Published - 2013 |