2022International Journal of Robust and Nonlinear ControlRequires access

Robust duality for the uncertain multitime control optimization problems

Ayushi Baranwal, Anurag Jayswal, Preeti

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Abstract

Abstract This article gives some new duality results for the multitime control optimization problem with data uncertainty (MCOPU). We formulate Wolfe and Mond‐Weir type robust dual problems for (MCOPU) and prove the weak robust duality theorem which states that the duality gap is positive and the strong robust duality theorem which shows the zero duality gap under convexity assumptions. Further, we also prove the converse robust duality result. Moreover, we give some nontrivial examples to verify the established results in this article.

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What this paper is about

Abstract This article gives some new duality results for the multitime control optimization problem with data uncertainty (MCOPU). We formulate Wolfe and Mond‐Weir type robust dual problems for (MCOPU) and prove the weak robust duality theorem which states that the duality gap is positive and the strong robust duality theorem which shows the zero duality gap under convexity assumptions. Further, we also prove the converse robust duality result. Moreover, we give some nontrivial examples to verify the established results in this article.

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Available abstract

Abstract This article gives some new duality results for the multitime control optimization problem with data uncertainty (MCOPU). We formulate Wolfe and Mond‐Weir type robust dual problems for (MCOPU) and prove the weak robust duality theorem which states that the duality gap is positive and the strong robust duality theorem which shows the zero duality gap under convexity assumptions. Further, we also prove the converse robust duality result. Moreover, we give some nontrivial examples to verify the established results in this article.

Key concepts: Duality gap, Wolfe duality, Duality (order theory), Strong duality, Converse, Weak duality, Perturbation function, Mathematics

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