Title
An Interior Point Algorithm for Mixed Complementarity Nonlinear Problems
Date Issued
01 November 2017
Access level
metadata only access
Resource Type
journal article
Publisher(s)
Springer Science and Business Media, LLC
Abstract
Nonlinear complementarity and mixed complementarity problems arise in mathematical models describing several applications in Engineering, Economics and different branches of physics. Previously, robust and efficient feasible directions interior point algorithm was presented for nonlinear complementarity problems. In this paper, it is extended to mixed nonlinear complementarity problems. At each iteration, the algorithm finds a feasible direction with respect to the region defined by the inequality conditions, which is also monotonic descent direction for the potential function. Then, an approximate line search along this direction is performed in order to define the next iteration. Global and asymptotic convergence for the algorithm is investigated. The proposed algorithm is tested on several benchmark problems. The results are in good agreement with the asymptotic analysis. Finally, the algorithm is applied to the elastic–plastic torsion problem encountered in the field of Solid Mechanics.
Start page
432
End page
449
Volume
175
Issue
2
Language
English
OCDE Knowledge area
Matemáticas
Scopus EID
2-s2.0-85029545331
Source
Journal of Optimization Theory and Applications
ISSN of the container
00223239
Sponsor(s)
Acknowledgements We thank the anonymous reviewer and A. Chapiro for help in improving the text. Angel E. R. Gutierrez was supported in part by FONDECYT “Generación Científica—Becas Nacionales— Fortalecimiento de Programas de doctorado en universidades peruanas” under Award 217-2014. José Herskovits was supported in part by CNPq and FAPERJ. Grigori Chapiro was supported in part by FAPEMIG under Award APQ-01377-15.
Sources of information: Directorio de Producción Científica Scopus