Error Bounds for Inverse Mixed Quasi-Variational Inequality via Generalized Residual Gap Functions

Yinfeng Zhang () and Guolin Yu
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Yinfeng Zhang: Institute of Applied Mathematics, North Minzu University, Yinchuan, Ningxia 750021, P. R. China
Guolin Yu: Institute of Applied Mathematics, North Minzu University, Yinchuan, Ningxia 750021, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2022, vol. 39, issue 02, 1-13

Abstract: In this paper, we investigate error bounds of an inverse mixed quasi variational inequality problem in Hilbert spaces. Under the assumptions of strong monotonicity of function couple, we obtain some results related to error bounds using generalized residual gap functions. Each presented error bound is an effective estimation of the distance between a feasible solution and the exact solution. Because the inverse mixed quasi-variational inequality covers several kinds of variational inequalities, such as quasi-variational inequality, inverse mixed variational inequality and inverse quasi-variational inequality, the results obtained in this paper can be viewed as an extension of the corresponding results in the related literature.

Keywords: Inverse mixed quasi-variational inequality; strong monotonicity; error bound; residual gap function (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0217595921500172

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