Affiliation:
1. Politecnico di Bari Dipartimento di Ingegneria Meccanica e Gestionale Italy
Abstract
Design optimization of complex structures entails tasks that oppose the usual constraints on time and computational resources. However, using optimization techniques is very useful because it allows engineers to obtain a large set of designs at low computational cost. Among the different optimization methods, sequential linear programming (SLP) is very popular because of its simplicity and because linear solvers (e.g. Simplex) are easily available. In spite of the inherent theoretical simplicity, well-coded SLP algorithms may outperform more sophisticated optimization methods. This paper describes the experience obtained in the design optimization of large-scale truss structures and beams with SLP-based algorithms. Sizing and configuration problems of structures under multiple loading conditions with up to 1000 design variables and 3500 constraints are considered. The relative performance and merits of some SLP-based algorithms are compared and the efficiency of an advanced SLP-based algorithm called ILEAML (improved linearization error amplitude move limits) is tested. ILEAML is also compared to the sequential quadratic programming (SQP) method, which is considered by theoreticians as probably the best theoretically founded optimization technique.
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献