Interactive multiobjective optimization with NIMBUS for decision making under uncertainty
Miettinen, K., Mustajoki, J., & Stewart, T. J. (2014). Interactive multiobjective optimization with NIMBUS for decision making under uncertainty. OR Spectrum, 36(1), 39-56. https://doi.org/10.1007/s00291-013-0328-5
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© Springer-Verlag Berlin Heidelberg 2013. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
We propose an interactive method for decision making under uncertainty,
where uncertainty is related to the lack of understanding about
consequences of actions. Such situations are typical, for example, in design
problems, where a decision maker has to make a decision about a
design at a certain moment of time even though the actual consequences
of this decision can be possibly seen only many years later. To overcome
the difficulty of predicting future events when no probabilities of events
are available, our method utilizes groupings of objectives or scenarios to
capture different types of future events. Each scenario is modeled as a
multiobjective optimization problem to represent different and conflicting
objectives associated with the scenarios. We utilize the interactive
classification-based multiobjective optimization method NIMBUS for assessing
the relative optimality of the current solution in different scenarios.
This information can be utilized when considering the next step of the
overall solution process. Decision making is performed by giving special
attention to individual scenarios. We demonstrate our method with an
example in portfolio optimization.
...
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