Name
Abstract | ||
|---|---|---|
Two approximation algorithms for solving convex vector optimization problems (CVOPs) are provided. Both algorithms solve the CVOP and its geometric dual problem simultaneously. The first algorithm is an extension of Benson's outer approximation algorithm, and the second one is a dual variant of it. Both algorithms provide an inner as well as an outer approximation of the (upper and lower) images. Only one scalar convex program has to be solved in each iteration. We allow objective and constraint functions that are not necessarily differentiable, allow solid pointed polyhedral ordering cones, and relate the approximations to an appropriate $$\epsilon $$ ∈ -solution concept. Numerical examples are provided. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10898-013-0136-0 | Journal of Global Optimization |
Keywords | Field | DocType |
Vector optimization,Multiple objective optimization,Convex programming,Duality,Algorithms,Outer approximation | Approximation algorithm,Mathematical optimization,Vector optimization,Mathematical analysis,Subderivative,Frank–Wolfe algorithm,Proper convex function,Conic optimization,Convex optimization,Convex analysis,Mathematics | Journal |
Volume | Issue | ISSN |
60 | 4 | Journal of Global Optimization 2014, Vol. 60 (4), 713-736 |
Citations | PageRank | References |
8 | 0.55 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreas Löhne | 1 | 8 | 0.55 |
| Birgit Rudloff | 2 | 24 | 2.83 |
| Firdevs Ulus | 3 | 13 | 1.37 |