Title
An Iterative Method for Finding the Least Solution to the Tensor Complementarity Problem.
Abstract
In this paper, we are concerned with finding the least solution to the tensor complementarity problem. When the involved tensor is strongly monotone, we present a way to estimate the nonzero elements of the solution in a successive manner. The procedure for identifying the nonzero elements of the solution gives rise to an iterative method of solving the tensor complementarity problem. In each iteration, we obtain an iterate by solving a lower-dimensional tensor equation. After finitely many iterations, the method terminates with a solution to the problem. Moreover, the sequence generated by the method is monotonically convergent to the least solution to the problem. We then extend this idea for general case and propose a sequential mathematical programming method for finding the least solution to the problem. Since the least solution to the tensor complementarity problem is the sparsest solution to the problem, the method can be regarded as an extension of a recent result by Luo et al. (Optim Lett 11:471–482, 2017). Our limited numerical results show that the method can be used to solve the tensor complementarity problem efficiently.
Year
DOI
Venue
2017
10.1007/s10957-017-1157-5
J. Optimization Theory and Applications
Keywords
Field
DocType
Tensor complementarity problem,Z-tensor,Least solution,Sparsest solution,Monotone convergence,90C33,15A72,65N12
Monotonic function,Mathematical optimization,Tensor (intrinsic definition),Tensor,Iterative method,Mathematical analysis,Strongly monotone,Complementarity theory,Mixed complementarity problem,Mathematics
Journal
Volume
Issue
ISSN
175
1
0022-3239
Citations 
PageRank 
References 
5
0.43
11
Authors
3
Name
Order
Citations
PageRank
Shuilian Xie150.43
Donghui Li238032.40
Hongru Xu3174.08