An Inexact Solution Approach for the Mathematical Program with Complementarity Constraints

We propose an approach based on a penalty formulation and a relaxation scheme for mathematical programs with complementarity constraints (MPCC). We discuss the convergence analysis with a new strong approximate stationarity concept. The convergence of the sequence of strong approximate stationary po...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2020 IEEE 6th International Conference on Optimization and Applications (ICOA) S. 1 - 6
Hauptverfasser: Azizi, Hicham, Kadrani, Abdeslam
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.04.2020
Schlagworte:
approximate stationarity
Convergence
Economics
Indexes
Mathematical programming with complementarity constraints
Optimization
penalization methods
Programming
regularization methods
Relaxation methods
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We propose an approach based on a penalty formulation and a relaxation scheme for mathematical programs with complementarity constraints (MPCC). We discuss the convergence analysis with a new strong approximate stationarity concept. The convergence of the sequence of strong approximate stationary points, generated by solving a family of regularized-penalized sub-problems, is investigated. Under the MPCC-Mangasarian-Fromovitz constraint qualifications (MPCC-MFCQ), we show that any accumulation point of the sequence of strong approximate stationary points of regularized-penalized sub-problems is a M-stationary point of the original MPCC.
DOI:10.1109/ICOA49421.2020.9094474