Publication: Projection-Based Local and Global Lipschitz Moduli of the Optimal Value in Linear Programming
Projection-Based Local and Global Lipschitz Moduli of the Optimal Value in Linear Programming
Date
Date
Date
Citations
Canovas, M. J., Gisbert, M. J., Klatte, D., & Parra, J. (2022). Projection-Based Local and Global Lipschitz Moduli of the Optimal Value in Linear Programming. Journal of Optimization Theory and Applications, 193(1–3), 280–299. https://doi.org/10.1007/s10957-021-01948-2
Abstract
Abstract
Abstract
In this paper, we use a geometrical approach to sharpen a lower bound given in [5] for the Lipschitz modulus of the optimal value of (finite) linear programs under tilt perturbations of the objective function. The key geometrical idea comes from orthogonally projecting general balls on linear subspaces. Our new lower bound provides a computable expression for the exact modulus (as far as it only depends on the nominal data) in two important cases: when the feasible set has extreme points and when we deal with the Euclidean norm. In th
Metrics
Downloads
Views
Citations
Additional indexing
Creators (Authors)
- Canovas, M J
- Gisbert, M J
- Klatte, Diethard
- Parra, J
Journal/Series Title
Journal/Series Title
Journal/Series Title
Volume
Volume
Volume
Number
Number
Number
Page range/Item number
Page range/Item number
Page range/Item number
Page end
Page end
Page end
Item Type
Item Type
Item Type
In collections
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Keywords
Scope
Scope
Scope
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
OA Status
OA Status
OA Status
Publisher DOI
Other Identification Number
Other Identification Number
Other Identification Number
Metrics
Downloads
Views
Citations
Citations
Canovas, M. J., Gisbert, M. J., Klatte, D., & Parra, J. (2022). Projection-Based Local and Global Lipschitz Moduli of the Optimal Value in Linear Programming. Journal of Optimization Theory and Applications, 193(1–3), 280–299. https://doi.org/10.1007/s10957-021-01948-2
