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Based on our references, it appears that many researchers have investigated the inverse variational inequality problem under the assumption of strong monotonicity. In this talk, inspired by the referenced works, we  study the inverse variational inequality problem by introducing new modified algorithms under the assumption of inverse monotonicity. Next, we study the variational inequality problem with the inverse variational inequality as constraint. In the final, we study the quasi-inverse variational inequality problem with constraint. The proposed modified algorithms that leverage the fixed point theorem of a nonexpansive mapping. By utilizing this theoretical framework, our algorithms aim to efficiently address the challenges posed by the inverse variational inequality problem and bilevel variational inequality problem.

More information : https://sites.google.com/g.ncyu.edu.tw/cschuang