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Variable Population Mopso Applied To Medical Visits

Author

Listed:
  • Lopez, Javier

    (III-LIDI (Institute of Research in Computer Science III-LIDI), National University of La Plata, Argentina)

  • Lanzarini, Laura

    (III-LIDI (Institute of Research in Computer Science III-LIDI), National University of La Plata, Argentina)

  • Fernandez Bariviera, Aurelio

    (Department of Business, Universitat Rovira i Virgili, Spain)

Abstract

Multi-objective optimization techniques are the ideal support tools for the decision-making process. They provide a set of optimal solutions for each of the significant aspects of the problem, thus summarizing the alternatives to be considered. Having a limited number of alternatives makes it easier for decision makers to perform their tasks, since they can focus their efforts towards the analysis of the available options. In this paper, the main characteristics of multi-objective optimization are summarized, and a real experience is described regarding the optimization of mobile units assignment at a health care company in Argentina using a new method based on swarm intelligence called varMOPSO.

Suggested Citation

  • Lopez, Javier & Lanzarini, Laura & Fernandez Bariviera, Aurelio, 2012. "Variable Population Mopso Applied To Medical Visits," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(1), pages 3-14, May.
    • Handle: RePEc:fzy:fuzeco:v:xvii:y:2012:i:1:p:3-14
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    More about this item

    Keywords

    customer evolutionary computation; swarm intelligence; particle swarm optimization; multi-objective function optimization;
    All these keywords.

    JEL classification:

    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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