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首页> 外文期刊>Journal of convex analysis >Primal Attainment in Convex Infinite Optimization Duality
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Primal Attainment in Convex Infinite Optimization Duality

机译:凸无限优化对偶的原始达成。

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This article provides results guarateeing that the optimal value of a given convex infinite optimization problem and its corresponding surrogate Lagrangian dual coincide and the primal optimal value is attainable. The conditions ensuring converse strong Lagrangian (in short, minsup) duality involve the weakly-inf-(locally) compactness of suitable functions and the linearity or relative closedness of some sets depending on the data. Applications are given to different areas of convex optimization, including an extension of the Clark-Duffin Theorem for ordinary convex programs.
机译:本文提供的结果可保证,给定凸无限优化问题的最优值及其对应的替代拉格朗日对偶重合,并且可以得到原始最优值。确保相反的强拉格朗日(简而言之,minsup)对偶性的条件涉及适当函数的弱inf-(局部)紧致性以及取决于数据的某些集合的线性或相对闭合性。凸优化的不同领域得到了应用,包括对普通凸程序的Clark-Duffin定理的扩展。

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