The Sparse Solution to KS-Tensor Complementarity Problems

2022/08/26 by Jingjing Sun, Shouqiang Du, Sun, Jingjing +5
Computer Science · Mathematics · #15A69 #90C33 #Computational Physics and Python Applications #FOS: Mathematics #Optimization and Control (math.OC) #Tensor decomposition and applications

paper · pdf · doi:10.48550/arxiv.2208.12444

openalex publication_date 2022/08/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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 l₀-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.

Related

• The Sparsest Solutions to Z-Tensor Complementarity Problems
• On sparse solution of tensor complementarity problem
• A mixed integer programming approach to the tensor complementarity problem
• The Horizontal Tensor Complementarity Problem
• A Lower Dimensional Linear Equation Approach to The M-Tensor Complementarity Problem