Steklov convexification and a trajectory method for global optimization of multivariate quartic polynomials-Reference-Cited by-同舟云学术

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Steklov convexification and a trajectory method for global optimization of multivariate quartic polynomials

Published:2020-07-04 Issue:1-2 Volume:189 Page:187-216
ISSN:0025-5610
Container-title:Mathematical Programming
language:en
Short-container-title:Math. Program.

Author:

Burachik Regina S.^ORCID,Kaya C. Yalçın^ORCID

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics,Software

Link

https://link.springer.com/content/pdf/10.1007/s10107-020-01536-8.pdf

Reference32 articles.

1. Arıkan, O., Burachik, R.S., Kaya, C.Y.: “Backward differential flow” may not converge to a global minimizer of polynomials. J. Optim. Theory Appl. 167, 401–408 (2015)

2. Arıkan, O., Burachik, R.S., Kaya, C.Y.: Steklov regularization and trajectory methods for univariate global optimization. J. Glob. Optim. 76(1), 91–120 (2020)

3. Attouch, H., Chbani, Z., Peypouquet, J., Redont, P.: Fast convergence of inertial dynamics and algorithms with asymptotic vanishing viscosity. Math. Program. 168(1–2), 123–175 (2018)

4. Borelli, R.L., Coleman, C.S.: Differential Equations: A Modeling Perspective. Wiley, Hoboken (2004)

5. Boţ, R.I., Csetnek, E.R.: Convergence rates for forward–backward dynamical systems associated with strongly monotone inclusions. J. Math. Anal. Appl. 457(2), 1135–1152 (2018)

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