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Efficient Second Order Optimization TechniqueFor Structural Optimization

Mohamed ElSayed, Spenser Anderson, K. W. Zumwalt

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Abstract

Constrained optimization methods classically fall into the categories of zeroor first-order algorithms. In this paper, a second order constrained optimization method, sequential quadratic programming with quadratic constraints (SQPQC), is developed. This method uses firstand second-order derivative information to build a second-order Taylor's series expansion to the constrained optimization problem. By using duality, the resulting subproblem, to find the search direction, is transformed into an unconstrained optimization problem with respect to the dual variables. Comparisons with robust feasible directions (RFD), for a curved plate shape optimization test case, is presented.

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What this paper is about

Constrained optimization methods classically fall into the categories of zeroor first-order algorithms. In this paper, a second order constrained optimization method, sequential quadratic programming with quadratic constraints (SQPQC), is developed. This method uses firstand second-order derivative information to build a second-order Taylor's series expansion to the constrained optimization problem. By using duality, the resulting subproblem, to find the search direction, is transformed into an unconstrained optimization problem with respect to the dual variables. Comparisons with robust feasible directions (RFD), for a curved plate shape optimization test case, is presented.

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Available abstract

Constrained optimization methods classically fall into the categories of zeroor first-order algorithms. In this paper, a second order constrained optimization method, sequential quadratic programming with quadratic constraints (SQPQC), is developed. This method uses firstand second-order derivative information to build a second-order Taylor's series expansion to the constrained optimization problem. By using duality, the resulting subproblem, to find the search direction, is transformed into an unconstrained optimization problem with respect to the dual variables. Comparisons with robust feasible directions (RFD), for a curved plate shape optimization test case, is presented.

Key concepts: Mathematical optimization, Taylor series, Quadratic programming, Optimization problem, Sequential quadratic programming, Constrained optimization, Continuous optimization, Test functions for optimization

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