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Smoothing Partially Exact Penalty Function of Biconvex Programming.
- Source :
- Asia-Pacific Journal of Operational Research; Aug2020, Vol. 37 Issue 4, pN.PAG-N.PAG, 27p
- Publication Year :
- 2020
-
Abstract
- In this paper, a smoothing partial exact penalty function of biconvex programming is studied. First, concepts of partial KKT point, partial optimum point, partial KKT condition, partial Slater constraint qualification and partial exactness are defined for biconvex programming. It is proved that the partial KKT point is equal to the partial optimum point under the condition of partial Slater constraint qualification and the penalty function of biconvex programming is partially exact if partial KKT condition holds. We prove the error bounds properties between smoothing penalty function and penalty function of biconvex programming when the partial KKT condition holds, as well as the error bounds between objective value of a partial optimum point of smoothing penalty function problem and its 𝜖 -feasible solution. So, a partial optimum point of the smoothing penalty function optimization problem is an approximately partial optimum point of biconvex programming. Second, based on the smoothing penalty function, two algorithms are presented for finding a partial optimum or approximate 𝜖 -feasible solution to an inequality constrained biconvex optimization and their convergence is proved under some conditions. Finally, numerical experiments show that a satisfactory approximate solution can be obtained by the proposed algorithm. [ABSTRACT FROM AUTHOR]
- Subjects :
- SMOOTHNESS of functions
ALGORITHMS
CONSTRAINED optimization
Subjects
Details
- Language :
- English
- ISSN :
- 02175959
- Volume :
- 37
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Asia-Pacific Journal of Operational Research
- Publication Type :
- Academic Journal
- Accession number :
- 145335626
- Full Text :
- https://doi.org/10.1142/S0217595920400187