Computational Optimization and Applications

, Volume 58, Issue 3, pp 757–779 | Cite as

Implementation aspects of interactive multiobjective optimization for modeling environments: the case of GAMS-NIMBUS



Interactive multiobjective optimization methods have provided promising results in the literature but still their implementations are rare. Here we introduce a core structure of interactive methods to enable their convenient implementation. We also demonstrate how this core structure can be applied when implementing an interactive method using a modeling environment. Many modeling environments contain tools for single objective optimization but not for interactive multiobjective optimization. Furthermore, as a concrete example, we present GAMS-NIMBUS Tool which is an implementation of the classification-based NIMBUS method for the GAMS modeling environment. So far, interactive methods have not been available in the GAMS environment, but with the GAMS-NIMBUS Tool we open up the possibility of solving multiobjective optimization problems modeled in the GAMS modeling environment. Finally, we give some examples of the benefits of applying an interactive method by using the GAMS-NIMBUS Tool for solving multiobjective optimization problems modeled in the GAMS environment.


Multiple objective programming Interactive methods  NIMBUS method Modeling languages Pareto optimality 



The research was partly supported by the Academy of Finland, Grant number 128495 (on the part of Vesa Ojalehto).

Supplementary material

10589_2014_9639_MOESM1_ESM.gms (7 kb)
Supplementary material 1 (gms 6 KB)


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Vesa Ojalehto
    • 1
  • Kaisa Miettinen
    • 1
  • Timo Laukkanen
    • 2
  1. 1.Department of Mathematical Information TechnologyUniversity of JyväskyläJyvaskylaFinland
  2. 2.Department of Energy TechnologyAalto University School of EngineeringAaltoFinland

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