A Line Search Exact Penalty Method Using Steering Rules

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Dehghan Nayeri, Maryam | 2011

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 42701 (02)
University: Sharif University of Technology
Department: Mathematical Sciences
Advisor(s): Mahdavi Amiri, Nezamoddin
Abstract:
Exact linear search algorithm recently have been proposed in the literature by Byrd, Lopez-Calvaz and Nocedal for solving nonlinear programming problems. Line search algorithms for nonlinear programming problems must include safeguards to have global convergence properties. We explain an exact penalization approach that extends the class of problems that can be solved with line search SQP methods. In the algorithm, the penalty parameter is adjusted at every iteration to ensure sufficient progress in linear feasibilility and to promote acceptance of the step. A trust region is used to assist in the determination of the penalty parameter. It is shown that the algorithm enjoys favorable global convergence properties. Numerical experiments illustrate the behavior of the algorithm on various difficult situations. We implement the method in Matlab environment and test the program on various problems. Numerical results show the effectiveness of the method
Keywords:
Nonlinearly Constrained Optimization ; Line Search ; Penalty Function ; Sequential Quadratic Programming (SQP) ; Steering Rules

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