Geometric Duality for Convex Vector Optimization Problems
Journal of convex analysis, Tome 20 (2013) no. 3, pp. 813-832
Voir la notice de l'article provenant de la source Heldermann Verlag
Geometric duality theory for multiple objective linear programming problems turned out to be very useful for the development of efficient algorithms to generate or approximate the whole set of nondominated points in the outcome space. This article extends the geometric duality theory to convex vector optimization problems.
Classification :
52A41, 52A20, 90C46, 90C29
Mots-clés : Geometric duality theory, vector optimization, Legendre-Fenchel conjugate, second-order subdifferential, Dupin indicatrix
Mots-clés : Geometric duality theory, vector optimization, Legendre-Fenchel conjugate, second-order subdifferential, Dupin indicatrix
@article{JCA_2013_20_3_JCA_2013_20_3_a9,
author = {F. Heyde},
title = {Geometric {Duality} for {Convex} {Vector} {Optimization} {Problems}},
journal = {Journal of convex analysis},
pages = {813--832},
publisher = {mathdoc},
volume = {20},
number = {3},
year = {2013},
url = {http://geodesic.mathdoc.fr/item/JCA_2013_20_3_JCA_2013_20_3_a9/}
}
F. Heyde. Geometric Duality for Convex Vector Optimization Problems. Journal of convex analysis, Tome 20 (2013) no. 3, pp. 813-832. http://geodesic.mathdoc.fr/item/JCA_2013_20_3_JCA_2013_20_3_a9/