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On Optimization over the Efficient Set in Linear Multicriteria Programming

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Abstract

The efficient set of a linear multicriteria programming problem can be represented by a reverse convex constraint of the form g(z)≤0, where g is a concave function. Consequently, the problem of optimizing some real function over the efficient set belongs to an important problem class of global optimization called reverse convex programming. Since the concave function used in the literature is only defined on some set containing the feasible set of the underlying multicriteria programming problem, most global optimization techniques for handling this kind of reverse convex constraint cannot be applied. The main purpose of our article is to present a method for overcoming this disadvantage. We construct a concave function which is finitely defined on the whole space and can be considered as an extension of the existing function. Different forms of the linear multicriteria programming problem are discussed, including the minimum maximal flow problem as an example.

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Authors and Affiliations

  1. Department of Mathematics, University of Trier, 54286, Trier, Germany

    R. Horst & N. V. Thoai

  2. Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, 305-8573, Japan

    Y. Yamamoto & D. Zenke

Authors
  1. R. Horst
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  2. N. V. Thoai
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  3. Y. Yamamoto
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  4. D. Zenke
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Corresponding author

Correspondence to N. V. Thoai.

Additional information

Communicated by G. Leitmann.

The research was partly done while the third author was visiting the Department of Mathematics, University of Trier with the support by the Alexander von Humboldt Foundation. He thanks the university as well as the foundation.

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Horst, R., Thoai, N.V., Yamamoto, Y. et al. On Optimization over the Efficient Set in Linear Multicriteria Programming. J Optim Theory Appl 134, 433–443 (2007). https://doi.org/10.1007/s10957-007-9219-8

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  • DOI: https://doi.org/10.1007/s10957-007-9219-8

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