Optimality conditions for approximate proper solutions in multiobjective optimization with polyhedral cones

C. Gutiérrez (), L. Huerga (), B. Jiménez () and V. Novo ()
Additional contact information
C. Gutiérrez: IMUVA (Institute of Mathematics of University of Valladolid)
L. Huerga: E.T.S.I. Industriales, Universidad Nacional de Educación a Distancia
B. Jiménez: E.T.S.I. Industriales, Universidad Nacional de Educación a Distancia
V. Novo: E.T.S.I. Industriales, Universidad Nacional de Educación a Distancia

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 28, issue 2, No 13, 526-544

Abstract: Abstract In this paper, we provide optimality conditions for approximate proper solutions of a multiobjective optimization problem, whose feasible set is given by a cone constraint and the ordering cone is polyhedral. A first class of optimality conditions is given by means of a nonlinear scalar Lagrangian and the second kind through a linear scalarization technique, under generalized convexity hypotheses, that lets us derive a Kuhn–Tucker multiplier rule.

Keywords: Multiobjective optimization; Optimality conditions; Approximate proper efficiency; Polyhedral ordering cone; Nonlinear Lagrangian; Linear scalarization; 90C25; 90C26; 90C29; 90C30; 90C46 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11750-020-00546-1

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