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Generalized higher-order cone-convex functions and higher-order duality in vector optimization

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Abstract

In this paper, we introduce a new class of higher-order cone-convex, \((K_1, K_2)\)-pseudoconvex and quasiconvex functions which encapsulates several already known functions. Higher-order sufficient optimality conditions have been established for a vector optimization problem over cones by using these functions, under weaker conditions on multipliers as compared to other papers in this domain. Wolfe type and Mond–Weir type higher-order duals are formulated and corresponding duality results are established. A number of previously studied problems appear as special cases of our primal-dual models. In case of nonlinear programming problem, our higher-order duals reduce to the corresponding higher-order duals given by Mangasarian (J Math Anal Appl 51:607–620, 1975) and Mond and Zhang (Generalized convexity, generalized monotonicity: recent results. Kluwer, Dordrecht, pp 357–372, 1998).

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Correspondence to Priyanka Yadav.

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Suneja, S.K., Sharma, S. & Yadav, P. Generalized higher-order cone-convex functions and higher-order duality in vector optimization. Ann Oper Res 269, 709–725 (2018). https://doi.org/10.1007/s10479-017-2470-y

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  • DOI: https://doi.org/10.1007/s10479-017-2470-y

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