Adaptive Global Algorithm for Solving Box-Constrained Non-convex Quadratic Minimization Problems-Reference-Cited by-同舟云学术

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Adaptive Global Algorithm for Solving Box-Constrained Non-convex Quadratic Minimization Problems

Published:2022-01 Issue:1 Volume:192 Page:360-378
ISSN:0022-3239
Container-title:Journal of Optimization Theory and Applications
language:en
Short-container-title:J Optim Theory Appl

Author:

Andjouh Amar,Bibi Mohand Ouamer

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Management Science and Operations Research,Control and Optimization

Link

https://link.springer.com/content/pdf/10.1007/s10957-021-01980-2.pdf

Reference37 articles.

1. Ajima, Y., Fujie, T.: A polyhedral approach for nonconvex quadratic programming problems with box constraints. J. Glob. Optim. 13, 151–170 (1998)

2. Best, M.J., Ding, B.: Global and local quadratic minimization. J. Glob. Optim. 10, 77–90 (1997)

3. Bibi, M.O., Ikeneche, N., Bentobache, M.: A hybrid direction algorithm for solving a convex quadratic problem. Int. J. Math. Oper. Res. 16(2), 159–178 (2020)

4. Bomze, I.M., Danninger, G.: A global optimization algorithm for concave quadratic programming problems. SIAM J. Optim. 3, 826–842 (1993)

5. Brahmi, B., Bibi, M.O.: Dual Support method for Solving convex quadratic programs. Optimization 59, 851–872 (2010)

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1. The Complexity of Computing KKT Solutions of Quadratic Programs;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

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