Generalized Polarity and Weakest Constraint Qualifications in Multiobjective Optimization

Oliver Stein () and Maximilian Volk ()
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Oliver Stein: Karlsruhe Institute of Technology (KIT)
Maximilian Volk: Karlsruhe Institute of Technology (KIT)

Journal of Optimization Theory and Applications, 2023, vol. 198, issue 3, No 11, 1156-1190

Abstract: Abstract In Haeser and Ramos (J Optim Theory Appl, 187:469–487, 2020), a generalization of the normal cone from single objective to multiobjective optimization is introduced, along with a weakest constraint qualification such that any local weak Pareto optimal point is a weak Kuhn–Tucker point. We extend this approach to other generalizations of the normal cone and corresponding weakest constraint qualifications, such that local Pareto optimal points are weak Kuhn–Tucker points, local proper Pareto optimal points are weak and proper Kuhn–Tucker points, respectively, and strict local Pareto optimal points of order one are weak, proper and strong Kuhn–Tucker points, respectively. The constructions are based on an appropriate generalization of polarity to pairs of matrices and vectors.

Keywords: Generalized polar cone; Generalized bipolar cone; Multiobjective stationarity condition; Multiobjective Kuhn–Tucker condition; Weakest constraint qualification; 90C29; 90C46 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10957-023-02256-7

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