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| Content Provider | Springer Nature Link |
|---|---|
| Author | Yang, Li Yu, Bo Li, YanXi |
| Copyright Year | 2015 |
| Abstract | This paper proposes a homotopy method based on a penalty function for solving nonlinear semidefinite programming problems. The penalty function is the composite function of an exponential penalty function, the eigenvalue function and a nonlinear operator mapping. Representations of its first and second order derivatives are given. Using the penalty function, a new homotopy is constructed. Global convergence of a smooth curve determined by the homotopy is proven under mild conditions. In the process of numerically tracing the curve, the method requires just the solution of a linear system of dimension $$n+2$$ , whereas a homotopy method proposed by Yang and Yu (Comput Optim Appl 56(1):81–96, 2013) requires a system of dimension $$n+m(m+1)/2+1$$ to be solved, where $$n$$ is the number of variables while $$m$$ is the order of constraint matrix. So, it is expected that the proposed method can improve the efficiency of the method proposed by Yang and Yu. Preliminary numerical experiments are presented and show that the considered algorithm is efficient for some nonlinear semidefinite programming problems. |
| Starting Page | 61 |
| Ending Page | 76 |
| Page Count | 16 |
| File Format | |
| ISSN | 09255001 |
| Journal | Journal of Global Optimization |
| Volume Number | 63 |
| Issue Number | 1 |
| e-ISSN | 15732916 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2015-02-08 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Homotopy method Global convergence Penalty function Nonlinear semidefinite programming Optimization Operations Research/Decision Theory Real Functions Computer Science |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Optimization Applied Mathematics Management Science and Operations Research Business, Management and Accounting Computer Science Applications |
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