Name
Abstract | ||
|---|---|---|
. Algorithms generating piecewise linear approximations of the nondominated set for general, convex and nonconvex, multicriteria
programs are developed. Polyhedral distance functions are used to construct the approximation and evaluate its quality. The
functions automatically adapt to the problem structure and scaling which makes the approximation process unbiased and self-driven.
Decision makers preferences, if available, can be easily incorporated but are not required by the procedure. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/s001860200217 | Math. Meth. of OR |
Keywords | Field | DocType |
multicriteria programs,approximation,nondominated set,dis- tance functions,multicriteria optimization,decision maker,distance function | Discrete mathematics,Approximation algorithm,Mathematical optimization,Piecewise linear approximation,Polyhedron,Regular polygon,Multicriteria analysis,Multi-objective optimization,Multiobjective programming,Scaling,Mathematics | Journal |
Volume | Issue | ISSN |
56 | 3 | 1432-2994 |
Citations | PageRank | References |
20 | 1.75 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kathrin Klamroth | 1 | 579 | 41.93 |
| Jørgen Tind | 2 | 149 | 22.29 |
| Margaret M. Wiecek | 3 | 213 | 22.90 |