6533b7d6fe1ef96bd12671c8
RESEARCH PRODUCT
Interactive Multiobjective Robust Optimization with NIMBUS
Kaisa MiettinenYue Zhou-kangasKarthik Sindhyasubject
Mathematical optimization021103 operations researchComputer sciencepareto-tehokkuuspäätöksenteko0211 other engineering and technologiesPareto principlemultiple criteria decision makingRobust optimization02 engineering and technologyrobustnessinteractive methodsDecision makerMinimaxTwo stagesrobust Pareto optimalitymonitavoiteoptimointiepävarmuusMultiobjective optimization problemRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingdescription
In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behaviors of the solutions, we visually present the objective function values. As a result, the decision maker can find a preferred balance between robustness and objective function values under the nominal case. peerReviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-01-01 |