A convergence proof for an affine-scaling algorithm for convex quadratic programming without nondegeneracy assumptions

1993 ◽  
Vol 60 (1-3) ◽  
pp. 69-79 ◽  
Author(s):  
Jie Sun
Keyword(s):  
Quadratic Programming ◽  
Convex Quadratic Programming ◽  
Affine Scaling ◽  
Convergence Proof ◽  
Affine Scaling Algorithm

A simplified global convergence proof of the affine scaling algorithm

1993 ◽  
Vol 46-47 (2) ◽  
pp. 443-482 ◽  
Author(s):  
R. D. C. Monteiro ◽  
T. Tsuchiya ◽  
Y. Wang
Keyword(s):  
Global Convergence ◽  
Affine Scaling ◽  
Convergence Proof ◽  
Affine Scaling Algorithm

scholarly journals A characterization of the weighted version of McEliece–Rodemich–Rumsey–Schrijver number based on convex quadratic programming

2015 ◽  
Vol 07 (04) ◽  
pp. 1550050
Author(s):  
Carlos J. Luz
Keyword(s):  
Quadratic Programming ◽  
Discrete Math ◽  
Convex Quadratic Programming ◽  
Stability Number ◽  
Weighted Version ◽  
Similar Characterization ◽  
Number Formula ◽  
Weighted Stability ◽  
Theta Number

For any graph [Formula: see text] Luz and Schrijver [A convex quadratic characterization of the Lovász theta number, SIAM J. Discrete Math. 19(2) (2005) 382–387] introduced a characterization of the Lovász number [Formula: see text] based on convex quadratic programming. A similar characterization is now established for the weighted version of the number [Formula: see text] independently introduced by McEliece, Rodemich, and Rumsey [The Lovász bound and some generalizations, J. Combin. Inform. Syst. Sci. 3 (1978) 134–152] and Schrijver [A Comparison of the Delsarte and Lovász bounds, IEEE Trans. Inform. Theory 25(4) (1979) 425–429]. Also, a class of graphs for which the weighted version of [Formula: see text] coincides with the weighted stability number is characterized.

Sign in / Sign up

Export Citation Format

Share Document