Open AccessPenalized NCP-functions for nonlinear complementarity problems and a scaling algorithm
Author(s) -
Jueyu Wang,
Chao Gu,
Guoqiang Wang
Publication year - 2022
Publication title -
journal of industrial and management optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.325
H-Index - 32
eISSN - 1553-166X
pISSN - 1547-5816
DOI - 10.3934/jimo.2021171
Subject(s) - nonlinear complementarity problem , scaling , complementarity (molecular biology) , algorithm , nonlinear system , stationary point , mixed complementarity problem , mathematical optimization , complementarity theory , mathematics , computer science , mathematical analysis , geometry , physics , quantum mechanics , biology , genetics
In this paper, we systematically study the properties of penalized NCP-functions in derivative-free algorithms for nonlinear complementarity problems (NCPs), and give some regular conditions for stationary points of penalized NCP-functions to be solutions of NCPs. The main contribution is to unify and generalize previous results. Based on one of above penalized NCP-functions, we analyze a scaling algorithm for NCPs. The numerical results show that the scaling can greatly improve the effectiveness of the algorithm.