On the use of a class of interior point algorithms in stochastic structural optimization

In this paper the feasibility of using a particular feasible direction interior point algorithm for solving reliability-based optimization problems of high dimensional stochastic dynamical systems is investigated. The optimal design problem is formulated in terms of an inequality constrained non-linear optimization problem. A class of interior point algorithms based on the solution of the first-order optimality conditions is considered here. For this purpose, a quasi-Newton iteration is used to solve the corresponding nonlinear system of equations. Several numerical examples are presented to illustrate the feasibility of the proposed methodology.

► A particular feasible direction algorithm is considered.
► Proposed scheme is applicable in high dimensional reliability problems.
► A small number of reliability evaluations is required.
► Flexibility of the algorithm is also observed in stochastic optimization.
► Proposed implementation provides an efficient tool for solving complex problems.
► Quasi-Newton type of iterations are implemented.