On the identification of local minimizers in inertia-controlling methods for quadratic programming

Technical Report · Sat Jul 01 00:00:00 EDT 1989

DOI:https://doi.org/10.2172/5466244· OSTI ID:5466244

Forsgren, A. L.; Gill, P. E.; Murray, W.

The verification of a local minimizer of a general (i.e., nonconvex) quadratic program is in general an NP-hard problem. The difficulty concerns the optimality of certain points (which we call dead points) at which the first-order necessary conditions for optimality are satisfied, but strict complementarity does not hold. One important class of methods for solving general quadratic programming problems are called inertia-controlling quadratic programming (ICQP) methods. We derive a computational scheme for proceeding at a dead point that is appropriate for a general ICQP method. 13 refs.

• Research Organization: Stanford Univ., CA (USA). Systems Optimization Lab.
• Sponsoring Organization: USDOD; DOE/ER; GGUSTF; National Science Foundation (NSF)
• DOE Contract Number: FG03-87ER25030
• OSTI ID: 5466244
• Report Number(s): SOL-89-11; ON: DE89017330; CNN: CCR-8413211; N00014-87-K-0142
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
NONLINEAR PROGRAMMING
ALGORITHMS
MATRICES
OPTIMIZATION
MATHEMATICAL LOGIC
PROGRAMMING
990300* - Information Handling
990210 - Supercomputers- (1987-1989)