The Sparse Solution to $\mathcal{KS}$-Tensor Complementarity Problems
Optimization and Control
2022-08-29 v1
Abstract
In view of the KS-tensor complementarity problem, the sparse solution of this problem is studied. Due to the nonconvexity and noncontinuity of the l_0-norm, it is a NP hard problem to find the sparse solution of the KS-tensor complementarity problem. In order to solve this problem, we transform it into a polynomial programming problem with constraints. Then we use the sequential quadratic programming (SQP) algorithm to solve this transformed problem. Numerical results show that the SQP algorithm can find the sparse solutions of the KS-tensor complementarity problem effectively.
Cite
@article{arxiv.2208.12444,
title = {The Sparse Solution to $\mathcal{KS}$-Tensor Complementarity Problems},
author = {Jingjing Sun and Shouqiang Du and Yuanyuan Chen and Yimin Wei},
journal= {arXiv preprint arXiv:2208.12444},
year = {2022}
}