Image Space Analysis for Constrained Inverse Vector Variational Inequalities via Multiobjective Optimization |
| |
| Authors: | Jiawei Chen Elisabeth Köbis Markus Köbis Jen-Chih Yao |
| |
| Institution: | 1.School of Mathematics and Statistics,Southwest University,Chongqing,China;2.Martin Luther University Halle-Wittenberg, Institute of Mathematics,Halle (Saale),Germany;3.Department of Mathematics and Computer Science,Freie universit?t Berlin,Berlin,Germany;4.Center for General Education,China Medical University,Taichung,Taiwan;5.Department of Mathematics,King Abdulaziz University,Jeddah,Saudi Arabia |
| |
| Abstract: | In this paper, we employ the image space analysis to study constrained inverse vector variational inequalities. First, sufficient and necessary optimality conditions for constrained inverse vector variational inequalities are established by using multiobjective optimization. A continuous nonlinear function is also introduced based on the oriented distance function and projection operator. This function is proven to be a weak separation function and a regular weak separation function under different parameter sets. Then, two alternative theorems are established, which lead directly to sufficient and necessary optimality conditions of the inverse vector variational inequalities. This provides a partial answer to an open question posed in Chen et al. (J Optim Theory Appl 166:460–479, 2015). |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
