A new Feasible Descent Cone (FDC) method for constrained optimization, previously restricted to linear objectives, is here generalized to include non-linear objective functions as well. In the basic and exact algorithm a sequence of descent steps is taken through the interior of the feasible region
-factor methods for nonregular inequality-constrained optimization problems
✍ Scribed by Ewa Szczepanik; Alexey Tret’yakov
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 547 KB
- Volume
- 69
- Category
- Article
- ISSN
- 0362-546X
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✦ Synopsis
The paper presents a new method for solving irregular optimization problems with inequality constraints. Our results are based on the construction of p-regularity theory and on reformulating the inequality constraints as equalities. Namely, by introducing the slack variables of corresponding degree we obtain the equality-constrained problem, where their gradients are linearly dependent, and for which the Lagrange optimality system is singular at the solution of the optimization problem. We have derived the p-factor Lagrange system for finding extremum point x * , and under new sufficient condition of nondegeneracy in singular case we have proved regularity of this p-factor Lagrange system at solution point (x * , y * , λ * ). At the end, we presented numerical scheme for general case.
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