| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 109.41 KB | Adobe PDF |
Orientador(es)
Resumo(s)
Mathematical Program with Complementarity Constraints (MPCC) finds applica- tion in many fields. As the complementarity constraints fail the standard Linear In- dependence Constraint Qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ), at any feasible point, the nonlinear programming theory may not be directly applied to MPCC. However, the MPCC can be reformulated as NLP problem and solved by nonlinear programming techniques. One of them, the Inexact Restoration (IR) approach, performs two independent phases in each iteration - the feasibility and the optimality phases.
This work presents two versions of an IR algorithm to solve MPCC. In the feasibility phase two strategies were implemented, depending on the constraints features. One gives more importance to the complementarity constraints, while the other considers the priority of equality and inequality constraints neglecting the complementarity ones. The optimality phase uses the same approach for both algorithm versions.
The algorithms were implemented in MATLAB and the test problems are from MACMPEC collection.
Descrição
Palavras-chave
MPCC Inexact restoration Mathematical problem with complementarity constraints NonLinear programming
Contexto Educativo
Citação
Editora
CMMSE - Computational and Mathematical Methods in Science and Engineering