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Higher order duality in vector optimization over cones

机译:锥向量优化中的高阶对偶

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摘要

In this paper higher order cone convex, pseudo convex, strongly pseudo convex, and quasiconvex functions are introduced. Higher order sufficient optimality conditions are given for a weak minimum, minimum, strong minimum and Benson proper minimum solution of a vector optimization problem. A higher order dual is associated and weak and strong duality results are established under these new generalized convexity assumptions.
机译:本文介绍了高阶锥凸,伪凸,强伪凸和拟凸函数。对于向量优化问题的弱最小,最小,强最小和Benson适当最小解,给出了更高阶的充分最优条件。在这些新的广义凸假设下,建立了更高阶对偶,并建立了弱和强对偶结果。

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