IMPROVED MULTILEVEL OPTIMIZATION APPROACH FOR THE DESIGN OF COMPLEX ENGINEERING SYSTEMS.

Multilevel optimization methods are being considered for the design of complex systems on distributed networks of computers or even parallel processors. An obstacle to the use of multilevel methods is that they can be computationally expensive because of the cycling necessary to account for the coupling between the subproblems. This research effort aims at increasing the efficiency of multilevel optimization by adapting two techniques widely used in one-level optimization: constraint approximation and temporary constraint deletion. These improvements are tested on 2, 10, and 52 bar planar trusses. The results show that for larger problems (approximately 100 variables and larger), the cost of analysis dominates the total cost so that multilevel optimization is no more expensive than one-level optimization. If parallel processing is used or the analysis process itself is decomposed, then multilevel optimization stands to become more economical than one-level optimization.