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Using box indices in supporting comparison in multiobjective optimization

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  • Miettinen, Kaisa
  • Molina, Julián
  • González, Mercedes
  • Hernández-Díaz, Alfredo
  • Caballero, Rafael

Abstract

Because of the conflicting nature of criteria or objectives, solving a multiobjective optimization problem typically requires interaction with a decision maker who can specify preference information related to the objectives in the problem in question. Due to the difficulties of dealing with multiple objectives, the way information is presented plays a very important role. Questions posed to the decision maker must be simple enough and information shown must be easy to understand. For this purpose, visualization and graphical representations can be useful and constitute one of the main tools used in the literature. In this paper, we propose to use box indices to represent information related to different solution alternatives of multiobjective optimization problems involving at least three objectives. Box indices are an intelligible and easy to handle way to represent data. They are based on evaluating the solutions in a natural and rough enough scale in order to let the decision maker easily recognize the main characteristics of a solution at a glance and to facilitate comparison of two or more solutions in an easily understandable way.

Suggested Citation

  • Miettinen, Kaisa & Molina, Julián & González, Mercedes & Hernández-Díaz, Alfredo & Caballero, Rafael, 2009. "Using box indices in supporting comparison in multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 197(1), pages 17-24, August.
  • Handle: RePEc:eee:ejores:v:197:y:2009:i:1:p:17-24
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    References listed on IDEAS

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    1. Jaszkiewicz, Andrzej & Slowinski, Roman, 1999. "The `Light Beam Search' approach - an overview of methodology and applications," European Journal of Operational Research, Elsevier, vol. 113(2), pages 300-314, March.
    2. Caballero, Rafael & Gonzalez, Mercedes & Guerrero, Flor M & Molina, Julian & Paralera, Concepcion, 2007. "Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1751-1763, March.
    3. A. M. Geoffrion & J. S. Dyer & A. Feinberg, 1972. "An Interactive Approach for Multi-Criterion Optimization, with an Application to the Operation of an Academic Department," Management Science, INFORMS, vol. 19(4-Part-1), pages 357-368, December.
    4. Gandibleux, Xavier, 1999. "Interactive multicriteria procedure exploiting a knowledge-based module to select electricity production alternatives: The CASTART system," European Journal of Operational Research, Elsevier, vol. 113(2), pages 355-373, March.
    5. Mareschal, Bertrand & Brans, Jean-Pierre, 1988. "Geometrical representations for MCDA," European Journal of Operational Research, Elsevier, vol. 34(1), pages 69-77, February.
    6. Kok, M. & Lootsma, F. A., 1985. "Pairwise-comparison methods in multiple objective programming, with applications in a long-term energy-planning model," European Journal of Operational Research, Elsevier, vol. 22(1), pages 44-55, October.
    7. Jurado, F. & Valverde, M., 2005. "Enhancing the electrical performance of a solid oxide fuel cell using multiobjective genetic algorithms," Renewable Energy, Elsevier, vol. 30(6), pages 881-902.
    8. Miettinen, Kaisa & Makela, Marko M., 2006. "Synchronous approach in interactive multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 170(3), pages 909-922, May.
    9. Beume, Nicola & Naujoks, Boris & Emmerich, Michael, 2007. "SMS-EMOA: Multiobjective selection based on dominated hypervolume," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1653-1669, September.
    10. M Köksalan & O Rizi, 2001. "A visual interactive approach for multiple criteria decision making with monotone utility functions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(6), pages 665-672, June.
    11. Korhonen, Pekka, 1988. "A visual reference direction approach to solving discrete multiple criteria problems," European Journal of Operational Research, Elsevier, vol. 34(2), pages 152-159, March.
    12. J.P. Hämäläinen & K. Miettinen & P. Tarvainen & J. Toivanen, 2003. "Interactive Solution Approach to a Multiobjective Optimization Problem in a Paper Machine Headbox Design," Journal of Optimization Theory and Applications, Springer, vol. 116(2), pages 265-281, February.
    13. Kathrin Klamroth & Kaisa Miettinen, 2008. "Integrating Approximation and Interactive Decision Making in Multicriteria Optimization," Operations Research, INFORMS, vol. 56(1), pages 222-234, February.
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    1. Rodríguez, Beatriz & Molina, Julián & Pérez, Fátima & Caballero, Rafael, 2012. "Interactive design of personalised tourism routes," Tourism Management, Elsevier, vol. 33(4), pages 926-940.

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