• Title/Summary/Keyword: V-invex

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ON SUFFICIENCY AND DUALITY FOR ROBUST OPTIMIZATION PROBLEMS INVOLVING (V, ρ)-INVEX FUNCTIONS

  • Kim, Moon Hee;Kim, Gwi Soo
    • East Asian mathematical journal
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    • v.33 no.3
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    • pp.265-269
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    • 2017
  • In this paper, we formulate a sufficient optimality theorem for the robust optimization problem (UP) under (V, ${\rho}$)-invexity assumption. Moreover, we formulate a Mond-Weir type dual problem for the robust optimization problem (UP) and show that the weak and strong duality hold between the primal problems and the dual problems.

PARAMETRIC DUALITY MODELS FOR DISCRETE MINMAX FRACTIONAL PROGRAMMING PROBLEMS CONTAINING GENERALIZED(${\theta},{\eta},{\rho}$)-V-INVEX FUNCTIONS AND ARBITRARY NORMS

  • Zalmai, G.J.
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.105-126
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    • 2007
  • The purpose of this paper is to construct several parametric duality models and prove appropriate duality results under various generalized (${\theta},{\eta},{\rho}$)-V-invexity assumptions for a discrete minmax fractional programming problem involving arbitrary norms.

GLOBAL PARAMETRIC SUFFICIENT OPTIMALITY CONDITIONS FOR DISCRETE MINMAX FRACTIONAL PROGRAMMING PROBLEMS CONTAINING GENERALIZED $({\theta},\;{\eta},\;{\rho})-V-INVEX$ FUNCTIONS AND ARBITRARY NORMS

  • Zalmai, G.J.
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.1-23
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    • 2007
  • The purpose of this paper is to develop a fairly large number of sets of global parametric sufficient optimality conditions under various generalized $({\theta},\;{\eta},\;{\rho})-V-invexity$ assumptions for a discrete minmax fractional programming problem involving arbitrary norms.

ON LINEARIZED VECTOR OPTIMIZATION PROBLEMS WITH PROPER EFFICIENCY

  • Kim, Moon-Hee
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.685-692
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    • 2009
  • We consider the linearized (approximated) problem for differentiable vector optimization problem, and then we establish equivalence results between a differentiable vector optimization problem and its associated linearized problem under the proper efficiency.

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