Predictor–corrector iterative algorithms for solving generalized mixed quasi-variational-like inclusion
作者:
Highlights:
•
摘要
By applying the concept of partially relaxed -strong monotonicity of set-valued mappings due to author and the auxiliary variational inequality technique, some new predictor–corrector iterative algorithms for solving generalized mixed quasi-variational-like inclusions are suggested and analyzed. The convergence of the algorithms only need the continuity and the partially relaxed -strongly monotonicity of set-valued mappings. The algorithm and convergence result are new, and generalize some recent known results in literatures.
论文关键词:Generalized mixed quasi-variational-like inclusion,Partially relaxed -strongly monotone,Predictor–corrector iterative algorithm
论文评审过程:Received 10 September 2003, Revised 26 October 2004, Available online 19 January 2005.
论文官网地址:https://doi.org/10.1016/j.cam.2004.11.036