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An SQP method for mathematical programs with vanishing constraints with strong convergence properties
We propose an SQP algorithm for mathematical programs with vanishing constraints which solves at each iteration a quadratic program with linear vanishing constraints. The algorithm is based on the newly developed concept of [Formula: see text] -stationarity (Benko and Gfrerer in Optimization 66(1):6...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5397537/ https://www.ncbi.nlm.nih.gov/pubmed/28479672 http://dx.doi.org/10.1007/s10589-017-9894-9 |
Sumario: | We propose an SQP algorithm for mathematical programs with vanishing constraints which solves at each iteration a quadratic program with linear vanishing constraints. The algorithm is based on the newly developed concept of [Formula: see text] -stationarity (Benko and Gfrerer in Optimization 66(1):61–92, 2017). We demonstrate how [Formula: see text] -stationary solutions of the quadratic program can be obtained. We show that all limit points of the sequence of iterates generated by the basic SQP method are at least M-stationary and by some extension of the method we also guarantee the stronger property of [Formula: see text] -stationarity of the limit points. |
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