Tuesday, 13:45 - 14:10 h, Room: H 1029


Kaisa Miettinen
Interactive Pareto Navigator method for nonconvex multiobjective optimization

Coauthors: Markus Hartikainen, Kathrin Klamroth


We describe a new interactive method called Nonconvex Pareto Navigator which extends the convex Pareto Navigator method for nonconvex multiobjective optimization problems. In the new method, a piecewise linear approximation of the Pareto optimal set is first generated using a relatively small set of Pareto optimal solutions. The decision maker (DM) can then navigate on the approximation and direct the search for interesting regions in the objective space. In this way, the DM can conveniently learn about the interdependencies between the conflicting objectives and possibly adjust one’s preferences. Besides nonconvexity, the new method contains more versatile options for directing the navigation. The Nonconvex Pareto Navigator method aims at supporting the learning phase of decision making. It is well-suited for computationally expensive problems because the navigation is computationally inexpensive to perform on the approximation. Once an interesting region has been found, the approximation can be refined in that region or the DM can ask for the closest actual Pareto optimal solution.


Talk 2 of the invited session Tue.2.H 1029
"Interactive multiobjective optimization" [...]
Cluster 15
"Multi-objective optimization" [...]


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