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STRUCTURAL OPTIMIZATION USING A NEW LOCAL APPROXIMATION METHOD
Author(s) -
CHICKERMANE H.,
GEA H. C.
Publication year - 1996
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/(sici)1097-0207(19960315)39:5<829::aid-nme884>3.0.co;2-u
Subject(s) - mathematical optimization , mathematics , sequence (biology) , convergence (economics) , approximation algorithm , sensitivity (control systems) , optimization problem , test functions for optimization , separable space , regular polygon , algorithm , multi swarm optimization , engineering , mathematical analysis , genetics , geometry , electronic engineering , economics , biology , economic growth
A new method for solving structural optimization problems using a local function approximation algorithm is proposed. This new algorithm, called the Generalized Convex Approximation (GCA), uses the design sensitivity information from the current and previous design points to generate a sequence of convex, separable subproblems. The paper contains the derivation of the parameters associated with the approximation and the formulation of the approximated problem. Numerical results from standard test problems solved using this method are presented. It is observed that this algorithm generates local approximations which lead to faster convergence for structural optimization problems.