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Recently an affine scaling, interior point algorithm ASL was developed for box constrained optimization problems with a single linear constraint (Gonzalez-Lima et al., SIAM J. Optim. 21:361–390, <CitationRef CitationID="CR7">2011</CitationRef>). This note extends the algorithm to handle more general polyhedral constraints. With a line...</citationref>
Persistent link: https://www.econbiz.de/10010998324
Persistent link: https://www.econbiz.de/10008925520
<Para ID="Par1">We present a local convergence analysis of Gauss-Newton method for solving nonlinear least square problems. Using more precise majorant conditions than in earlier studies such as Chen (Comput Optim Appl 40:97–118, <CitationRef CitationID="CR8">2008</CitationRef>), Chen and Li (Appl Math Comput 170:686–705, <CitationRef CitationID="CR9">2005</CitationRef>), Chen and Li (Appl...</citationref></citationref></para>
Persistent link: https://www.econbiz.de/10011241270
In this work we propose a class of quasi-Newton methods to minimize a twice differentiable function with Lipschitz continuous Hessian. These methods are based on the quadratic regularization of Newton’s method, with algebraic explicit rules for computing the regularizing parameter. The...
Persistent link: https://www.econbiz.de/10011241274
We propose a new nonmonotone filter method to promote global and fast local convergence for sequential quadratic programming algorithms. Our method uses two filters: a standard, global g-filter for global convergence, and a local nonmonotone l-filter that allows us to establish fast local...
Persistent link: https://www.econbiz.de/10010896525