A new class of strong mixed vector GQVIP-generalized quasi-variational inequality problems in fuzzy environment with regularized gap functions based error bounds

2021 ◽  
Vol 381 ◽  
pp. 113055 ◽  
Author(s):  
Nguyen Van Hung ◽  
Vo Minh Tam ◽  
Yong Zhou
2021 ◽  
Vol 6 (2) ◽  
pp. 1800-1815
Author(s):  
S. S. Chang ◽  
◽  
Salahuddin ◽  
M. Liu ◽  
X. R. Wang ◽  
...  

Author(s):  
Yinfeng Zhang ◽  
Guolin Yu

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.


2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Xin Zuo ◽  
Hong-Zhi Wei ◽  
Chun-Rong Chen

Continuity (both lower and upper semicontinuities) results of the Pareto/efficient solution mapping for a parametric vector variational inequality with a polyhedral constraint set are established via scalarization approaches, within the framework of strict pseudomonotonicity assumptions. As a direct application, the continuity of the solution mapping to a parametric weak Minty vector variational inequality is also discussed. Furthermore, error bounds for the weak vector variational inequality in terms of two known regularized gap functions are also obtained, under strong pseudomonotonicity assumptions.


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