학술논문

Combining the regularization strategy and the SQP to solve MPCC - a MATLAB implementation
Document Type
Working Paper
Source
Journal of Computational and Applied Mathematics, 235(18), 5348--5356 (2011)
Subject
Mathematics - Optimization and Control
Language
Abstract
Mathematical Program with Complementarity Constraints (MPCC) plays a very important role in many fields such as engineering design, economic equilibrium, multilevel game, and mathematical programming theory itself. In theory its constraints fail to satisfy a standard constraint qualification such as the linear independence constraint qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ) at any feasible point. As a result, the developed nonlinear programming theory may not be applied to MPCC class directly. Nowadays, a natural and popular approach is try to find some suitable approximations of an MPCC so that it can be solved by solving a sequence of nonlinear programs. This work aims to solve the MPCC using nonlinear programming techniques, namely the SQP and the regularization scheme. Some algorithms with two iterative processes, the inner and the external, were developed. A set of AMPL problems from MacMPEC database \cite{MacMPEC} were tested. The algorithms performance comparative analysis was carried out.
Comment: This is a preprint of a paper whose final and definite form is in Journal of Computational and Applied Mathematics