Multibody Dynamic Response Optimization with ALM and Approximate Line Search
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This paper presents an efficient approach for dynamic responseoptimization based on the ALM method. In this approach, an approximateaugmented Lagrangian is employed for line searches while an exactaugmented Lagrangian is used for finding search directions. An importantfeature of this study is that the approximate augmented Lagrangian forline search is composed of the linearized cost and constraint functionsprojected on the search direction. The quality of this approximationshould be good since an approximate penalty term is found to have almostsecond-order accuracy near the optimum. Quasi-Newton and conjugategradient algorithms are used to find exact search directions and a goldensection method followed by a cubic polynomial approximation is employedfor line search. The numerical performance of the proposed approach isinvestigated by solving eight typical dynamic response optimizationproblems and comparing the results with those in the literature. Thiscomparison shows that the suggested approach is robust and efficient.
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