Regularized gap functions and error bounds for split mixed vector quasivariational inequality problems

Author(s):  
Nguyen Van Hung ◽  
Vo Minh Tam ◽  
Dumitru Baleanu
2020 ◽  
Vol 16 (3) ◽  
pp. 1261-1272
Author(s):  
Minghua Li ◽  
◽  
Chunrong Chen ◽  
Shengjie Li ◽  

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.


Author(s):  
Nguyen Van Hung ◽  
Vicente Novo ◽  
Vo Minh Tam

AbstractThe aim of this paper is to establish new results on the error bounds for a class of vector equilibrium problems with partial order provided by a polyhedral cone generated by some matrix. We first propose some regularized gap functions of this problem using the concept of $$\mathcal {G}_{A}$$ G A -convexity of a vector-valued function. Then, we derive error bounds for vector equilibrium problems with partial order given by a polyhedral cone in terms of regularized gap functions under some suitable conditions. Finally, a real-world application to a vector network equilibrium problem is given to illustrate the derived theoretical results.


2019 ◽  
Vol 16 (3) ◽  
pp. 91
Author(s):  
Vo Minh Tam ◽  
Nguyen Huynh Vu Duy ◽  
Nguyen Kim Phat

This paper introduces regularized gap functions for a class of generalized mixed weak vector quasiequilibrium problems. Then, error boundsfor the concerning problems via regularized gap functions are established. Someexamples are provided to illustrate the results.


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