Name
Abstract | ||
|---|---|---|
This chapter describes various approaches to the use of evolutionary algorithms and other metaheuristics in interactive multiobjective
optimization. We distinguish the traditional approach to interactive analysis with the use of single objective metaheuristics,
the semi-a posteriori approach with interactive selection from a set of solutions generated by a multiobjective metaheuristic,
and specialized interactive multiobjective metaheuristics in which the DM’s preferences are interactively expressed during
the run of the method. We analyze properties of each of the approaches and give examples from the literature.
|
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-88908-3_7 | Dagstuhl Seminars |
Keywords | Field | DocType |
traditional approach,specialized interactive multiobjective metaheuristics,evolutionary algorithm,semi-a posteriori approach,interactive analysis,interactive multiobjective evolutionary algorithms,various approach,single objective metaheuristics,interactive multiobjective optimization,multiobjective metaheuristic,interactive selection,multiobjective optimization | Interactive analysis,Evolutionary algorithm,Computer science,Multi-objective optimization,Differential evolution,Artificial intelligence,Single objective,Machine learning,Metaheuristic | Conference |
Volume | ISSN | Citations |
5252 | 0302-9743 | 14 |
PageRank | References | Authors |
0.86 | 23 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Jaszkiewicz | 1 | 660 | 50.68 |
| Jürgen Branke | 2 | 2391 | 181.04 |