A Trust Region Interior Point Algorithm for Truss Structural Optimization Problems

The use of optimization in a simulation-based design of automotive, aerospace and consumer products has become a common trend today. Designers are faced with the continuous challenge of reducing manufacturing costs and design cycle times while improving the systems performance and reliability. In practical design, sequential linear programming (SLP) is very popular because of its inherent simplicity and easy availability. However, the inherent conceptual simplicity makes the SLP techniques not globally convergent. This research presents a new algorithm that uses a linearization error and an interior point trust-region method in SLP to truss structures that is both considered sizing and configuration problems. The algorithm may be suitable for large optimization problems where time is a constraint and the optimization may be stopped before convergence is achieved. Results of application studies are presented, illustrating the applicability of the proposed algorithm.