On minimizing objective and KKT error in a filter line search strategy for an interior point method

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6784 LNCS, Issue PART 3, 2011, Pages 231-244

  Costa, M Fernanda P ^a   Fernandes, Edite M G P ^a  

^a UNIVERSITY OF MINHO   (Portugal)

Author keywords

Filter method; Interior point method; Line search; Nonlinear programming

Indexed keywords

FILTER LINE SEARCHES; FILTER METHOD; FILTER STRATEGY; GLOBAL CONVERGENCE; INTERIOR POINT; INTERIOR POINT METHOD; INTERIOR POINT METHODS; KARUSH KUHN TUCKERS; KKT CONDITION; LINE SEARCHES; NUMERICAL STUDIES; OBJECTIVE FUNCTIONS; OPTIMALITY; PRIMAL-DUAL; TWO-DIMENSIONAL FILTERS;

CONVERGENCE OF NUMERICAL METHODS; LARGE SCALE SYSTEMS; OPTIMIZATION;

QUADRATIC PROGRAMMING;

EID: 79960306250     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21931-3_19     Document Type: Conference Paper

References (15)

1. Benson, H.Y., Vanderbei, R.J., Shanno, D.F.: Interior-point methods for nonconvex nonlinear programming:filter methods and merit functions. Computational Optimization and Applications 23, 257-272 (2002)
2. Costa, M.F.P., Fernandes, E.M.G.P.: Comparison of interior point filter line search strategies for constrained optimization by performance profiles. International Journal of Mathematics Models and Methods in Applied Sciences 1, 111-116 (2007)
3. Costa, M.F.P., Fernandes, E.M.G.P.: Practical implementation of an interior point nonmonotone line search filter method. International Journal of Computer Mathematics 85, 397-409 (2008)
4. Dolan, E.D., Moré, J.J.: Benchmarking optimization software with performance profiles. Mathematical Programming 91, 201-213 (2002)
5. Fletcher, R., Leyffer, S.: Nonlinear programming without a penalty function. Mathematical Programming 91, 239-269 (2002)
6. Fletcher, R., Leyffer, S., Toint, P.: A brief history of filter methods, Report ANL/MCS-P1372-0906, Argonne National Laboratory (2006)
7. Fourer, R., Gay, D.M., Kernighan, B.: A modeling language for mathematical programming. Management Science 36, 519-554 (1990)
8. Gould, N.I.M., Orban, D., Sartenaer, A., Toint, P.L.: Superlinear convergence of primal-dual interior point algorithms for nonlinear programming. SIAM Journal on Optimization 11, 974-1002 (2001)
9. Shanno, D.F., Vanderbei, R.J.: Interior-point methods for nonconvex nonlinear programming: orderings and higher-order methods. Mathematical Programming B 87, 303-316 (2000)
10. Ulbrich, M., Ulbrich, S., Vicente, L.N.: A globally convergent primal-dual interior-point filter method for nonlinear programming. Mathematical Programming 100, 379-410 (2004)
11. Vanderbei, R.J.: LOQO: An interior-code for quadratic programming. Technical report SOR-94-15, Princeton University, Statistics and Operations Research (1998)
12. Vanderbei, R.J., Shanno, D.F.: An interior-point algorithm for nonconvex nonlinear programming. Computational Optimization and Applications 13, 231-252 (1999)
13. Wächter, A., Biegler, L.T.: Line search filter methods for nonlinear programming: motivation and global convergence. SIAM Journal on Optimization 16, 1-31 (2005)
14. Wächter, A., Biegler, L.T.: Line search filter methods for nonlinear programming: local convergence. SIAM Journal on Optimization 16, 32-48 (2005)
15. Wächter, A., Biegler, L.T.: On the implementation of an interior-point filter linesearch algorithm for large-scale nonlinear programming. Mathematical Programming 106, 25-57 (2007)