Interactive multiobjective optimization with NIMBUS for decision making under uncertainty

  • Authors:

  • Kaisa Miettinen;Jyri Mustajoki;Theodor J. Stewart

  • Affiliations:

  • Department of Mathematical Information Technology, University of Jyväskylä, University of Jyväskylä, Finland 40014;Department of Automation Science and Engineering, Tampere University of Technology, Tampere, Finland 33101 and Finnish Environmental Institute, Freshwater Centre, Helsinki, Finland 00251;Department of Statistical Sciences, University of Cape Town, Rondebosch, South Africa 7701

  • Venue:
  • OR Spectrum
  • Year:
  • 2014

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Abstract

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.