Please use this identifier to cite or link to this item:
|Title:||Infeasible potential reduction algorithms for semidefinite programming|
|Keywords:||Infeasible potential reduction algorithms|
|Source:||Zhao, X.-Y.,Toh, K.-C. (2012-10). Infeasible potential reduction algorithms for semidefinite programming. Pacific Journal of Optimization 8 (4) : 725-753. ScholarBank@NUS Repository.|
|Abstract:||We design infeasible potential reduction algorithms for primal semidefinite programming (SDP) problems that simultaneously seek feasibility and optimality. The algorithms are based on those in [Anstre- icher, Math. Prog. 52 (1991), pp.429-439] and [Todd, Math. Prog. 59 (1993), pp.133-150] for linear programming. Because a dual algorithm is expected to be computationally advantageous for large sparse problems, we also propose a dual infeasible potential reduction algorithm for dual SDP problems. We analyze the convergence of the algorithms, and implement them to compare their relative performance. © 2012 Yokohama Publishers.|
|Source Title:||Pacific Journal of Optimization|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 23, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.