Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty

This article investigates robust optimality conditions and duality results for a class of nonsmooth multiobjective programming problems with vanishing constraints under data uncertainty (UNMPVC). Mathematical programming problems with vanishing constraints constitute a distinctive class of constrain...

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Main Authors: Balendu Bhooshan Upadhyay, Shubham Kumar Singh, I. M. Stancu-Minasian, Andreea Mădălina Rusu-Stancu
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Algorithms
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Online Access:https://www.mdpi.com/1999-4893/17/11/482
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author Balendu Bhooshan Upadhyay
Shubham Kumar Singh
I. M. Stancu-Minasian
Andreea Mădălina Rusu-Stancu
author_facet Balendu Bhooshan Upadhyay
Shubham Kumar Singh
I. M. Stancu-Minasian
Andreea Mădălina Rusu-Stancu
author_sort Balendu Bhooshan Upadhyay
collection DOAJ
description This article investigates robust optimality conditions and duality results for a class of nonsmooth multiobjective programming problems with vanishing constraints under data uncertainty (UNMPVC). Mathematical programming problems with vanishing constraints constitute a distinctive class of constrained optimization problems because of the presence of complementarity constraints. Moreover, uncertainties are inherent in various real-life problems. The aim of this article is to identify an optimal solution to an uncertain optimization problem with vanishing constraints that remains feasible in every possible future scenario. Stationary conditions are necessary conditions for optimality in mathematical programming problems with vanishing constraints. These conditions can be derived under various constraint qualifications. Employing the properties of convexificators, we introduce generalized standard Abadie constraint qualification (GS-ACQ) for the considered problem, UNMPVC. We introduce a generalized robust version of nonsmooth stationary conditions, namely a weakly stationary point, a Mordukhovich stationary point, and a strong stationary point (RS-stationary) for UNMPVC. By employing GS-ACQ, we establish the necessary conditions for a local weak Pareto solution of UNMPVC. Moreover, under generalized convexity assumptions, we derive sufficient optimality criteria for UNMPVC. Furthermore, we formulate the Wolfe-type and Mond–Weir-type robust dual models corresponding to the primal problem, UNMPVC.
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spelling doaj-art-6caee0a038314de4a140998f5c9ebda42025-08-20T02:08:07ZengMDPI AGAlgorithms1999-48932024-10-01171148210.3390/a17110482Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data UncertaintyBalendu Bhooshan Upadhyay0Shubham Kumar Singh1I. M. Stancu-Minasian2Andreea Mădălina Rusu-Stancu3Department of Mathematics, Indian Institute of Technology Patna, Bihar 801106, IndiaDepartment of Mathematics, Indian Institute of Technology Patna, Bihar 801106, India“Gheorghe Mihoc-Caius Iacob” Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy, 050711 Bucharest, Romania“Gheorghe Mihoc-Caius Iacob” Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy, 050711 Bucharest, RomaniaThis article investigates robust optimality conditions and duality results for a class of nonsmooth multiobjective programming problems with vanishing constraints under data uncertainty (UNMPVC). Mathematical programming problems with vanishing constraints constitute a distinctive class of constrained optimization problems because of the presence of complementarity constraints. Moreover, uncertainties are inherent in various real-life problems. The aim of this article is to identify an optimal solution to an uncertain optimization problem with vanishing constraints that remains feasible in every possible future scenario. Stationary conditions are necessary conditions for optimality in mathematical programming problems with vanishing constraints. These conditions can be derived under various constraint qualifications. Employing the properties of convexificators, we introduce generalized standard Abadie constraint qualification (GS-ACQ) for the considered problem, UNMPVC. We introduce a generalized robust version of nonsmooth stationary conditions, namely a weakly stationary point, a Mordukhovich stationary point, and a strong stationary point (RS-stationary) for UNMPVC. By employing GS-ACQ, we establish the necessary conditions for a local weak Pareto solution of UNMPVC. Moreover, under generalized convexity assumptions, we derive sufficient optimality criteria for UNMPVC. Furthermore, we formulate the Wolfe-type and Mond–Weir-type robust dual models corresponding to the primal problem, UNMPVC.https://www.mdpi.com/1999-4893/17/11/482multiobjective optimizationrobust optimizationvanishing constraintsPareto efficiency conditionsdualityconvexificators
spellingShingle Balendu Bhooshan Upadhyay
Shubham Kumar Singh
I. M. Stancu-Minasian
Andreea Mădălina Rusu-Stancu
Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty
Algorithms
multiobjective optimization
robust optimization
vanishing constraints
Pareto efficiency conditions
duality
convexificators
title Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty
title_full Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty
title_fullStr Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty
title_full_unstemmed Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty
title_short Robust Optimality and Duality for Nonsmooth Multiobjective Programming Problems with Vanishing Constraints Under Data Uncertainty
title_sort robust optimality and duality for nonsmooth multiobjective programming problems with vanishing constraints under data uncertainty
topic multiobjective optimization
robust optimization
vanishing constraints
Pareto efficiency conditions
duality
convexificators
url https://www.mdpi.com/1999-4893/17/11/482
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