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Ordered weighted enhancement of preference modeling in the reference point method for multiple criteria optimization

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Abstract

The reference point method is an interactive technique for multiple criteria optimization problems. It is based on the optimization of the scalarizing achievement function built as the augmented max–min aggregation of individual outcomes with respect to the given reference levels. Actually, the worst individual achievement is optimized, but regularized with the term representing the average achievement. In order to avoid inconsistencies caused by the regularization, we apply the ordered weighted averages (OWA) with monotonic weights to combine all the individual achievements. Further, following the concept of the weighted OWA (WOWA), we incorporate the importance weighting of several achievements into the RPM. We show that the resulting WOWA RPM can be quite effectively implemented as an extension of the original constraints and criteria with simple linear inequalities.

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Acknowledgments

The research was partially supported by the Polish Ministry of Science and Higher Education under the research grant N N516 4307 33.

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Authors and Affiliations

  1. Institute of Control and Computation Engineering, Warsaw University of Technology, 00-665, Warsaw, Poland

    Włodzimierz Ogryczak

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  1. Włodzimierz Ogryczak
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Correspondence to Włodzimierz Ogryczak.

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Ogryczak, W. Ordered weighted enhancement of preference modeling in the reference point method for multiple criteria optimization. Soft Comput 14, 435–450 (2010). https://doi.org/10.1007/s00500-009-0457-6

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