Abstract.
Algorithms generating piecewise linear approximations of the nondominated set for general, convex and nonconvex, multicriteria programs are developed. Polyhedral distance functions are used to construct the approximation and evaluate its quality. The functions automatically adapt to the problem structure and scaling which makes the approximation process unbiased and self-driven. Decision makers preferences, if available, can be easily incorporated but are not required by the procedure.
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Manuscript received: September 2001/Final version received: March 2002
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Klamroth, K., Tind, J. & Wiecek, M. Unbiased approximation in multicriteria optimization. Mathematical Methods of OR 56, 413–437 (2003). https://doi.org/10.1007/s001860200217
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DOI: https://doi.org/10.1007/s001860200217