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On the Sub Convexlike Optimization Problems
Version 1
: Received: 14 June 2023 / Approved: 15 June 2023 / Online: 15 June 2023 (12:53:52 CEST)
A peer-reviewed article of this Preprint also exists.
Zeng, R. On Sub Convexlike Optimization Problems. Mathematics 2023, 11, 2928. Zeng, R. On Sub Convexlike Optimization Problems. Mathematics 2023, 11, 2928.
Abstract
In this paper, we prove that the sub convexlikeness introduced by V. Jeyakumar [1], and the subconvexlikeness defined in V. Jeyakumar [2] are equivalent in loccallly convex topological spaces. And then, we work with set-valued vector optimization problems and obtain some vector saddle-point theorems and vector Lagrangian theorems.
Keywords
locally convex topological space, subconvexlikeness; sub convexlikeness; vector Lagrangian multiplier theorems; vector saddle-point theorems
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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