Optimization Methods and Software
ISSNs: 1029-4937
Taylor & Francis
Scopus rating (2022): CiteScore 4.2 SJR 1.079 SNIP 1.803
Journal
| Titles |
|
|---|---|
| ISSNs | 1029-4937 |
| Additional searchable ISSN | 1055-6788 |
| Publisher | Taylor & Francis |
| ZDB-ID | 1468203-5 |
Related content
- Research output
Toward state estimation by high gain differentiators with automatic differentiation
Röbenack, K. & Gerbet, D., 14 Mar 2024, (E-pub ahead of print) In: Optimization Methods and Software. p. 1-16Research output: Contribution to journal › Research article › Invited › peer-review
Nonconvex equilibrium models for energy markets: exploiting price information to determine the existence of an equilibrium
Grübel, J., Huber, O., Hümbs, L., Klimm, M., Schmidt, M. & Schwartz, A., 2023, In: Optimization Methods and Software. 38, 1, p. 153-183 31 p.Research output: Contribution to journal › Research article › Contributed › peer-review
Semismooth Newton-type method for bilevel optimization: global convergence and extensive numerical experiments
Fischer, A., Zemkoho, A. B. & Zhou, S., 2022, In: Optimization Methods and Software. 37, 5, p. 1770-1804 35 p.Research output: Contribution to journal › Research article › Contributed › peer-review
A study of one-parameter regularization methods for mathematical programs with vanishing constraints
Hoheisel, T., Pablos, B., Pooladian, A., Schwartz, A. & Steverango, L., 2020, In: Optimization Methods and Software. 2020Research output: Contribution to journal › Research article › Contributed › peer-review
Efficient optimization of hyper-parameters for least-squares support vector regression
Fischer, A., Langensiepen, G., Luig, K., Strasdat, N. & Thies, T., 2015, In: Optimization Methods and Software. 30, p. 1095-1108 14 p.Research output: Contribution to journal › Research article › Contributed › peer-review