New LP-based local and global algorithms for continuous and mixed-integer nonconvex quadratic programming

Author:

Bentobache MohandORCID,Telli Mohamed,Mokhtari Abdelkader

Publisher

Springer Science and Business Media LLC

Subject

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

Reference43 articles.

1. Absil, P.-A., Tits, A.L.: Newton-KKT interior-point methods for indefinite quadratic programming. Comput. Optim. Appl. 36, 5–41 (2007)

2. Bentobache, M., Bibi, M.O.: Numerical methods of linear and quadratic programming: theory and algorithms. French Academic Editions, Germany (2016) (in French)

3. Bentobache, M., Telli, M., Mokhtari A.: A simplex algorithm with the smallest index rule for concave quadratic programming. In: proceedings of the Eighth International Conference on Advanced Communications and Computation, INFOCOMP 2018, Barcelona, Spain, July 22–26, pp. 88–93 (2018)

4. Bentobache, M., Telli, M., Mokhtari, A.: A sequential linear programming algorithm for continuous and mixed-integer nonconvex quadratic programming. In: Le Thi, H.A., et al. (eds.) Optimizatin of Complex Systems: Theory, Models, Algorithms and Applications 991, 26–36. Springer, Cham (2020)

5. Bertsekas, D.P.: Nonlinear Programming. Second Athena Scientific, Belmont (1999)

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