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Generalized Univex Functions in Nonsmooth Multiobjective Optimization

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Journal of Mathematical Modelling and Algorithms in Operations Research

Abstract

In this paper, we have considered a nonsmooth multiobjective optimization problem where the objective and constraint functions involved are directionally differentiable. A new class of generalized functions (d − ρ − η − θ)-type I univex is introduced which generalizes many earlier classes cited in literature. Based upon these generalized functions, we have derived weak, strong, converse and strict converse duality theorems for mixed type multiobjective dual program in order to relate the efficient and weak efficient solutions of primal and dual problem.

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Correspondence to Pallavi Kharbanda.

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Kharbanda, P., Agarwal, D. & Sinha, D. Generalized Univex Functions in Nonsmooth Multiobjective Optimization. J Math Model Algor 12, 393–406 (2013). https://doi.org/10.1007/s10852-013-9218-8

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  • DOI: https://doi.org/10.1007/s10852-013-9218-8

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