Comparison of heuristic convergence strategies for multidisciplinary analysis

摘要

This work develops and compares heuristic convergence strategies for complex, coupled, multidisciplinary analysis. ^A convergence strategy is a method for ordering the execution of the subproblems in a multidisciplinary analysis to produce a convergence. ^The aim of this investigation is to provide guidance on which strategies to use in particular multidisciplinary design situations to minimize the time or cost of a system-level optimization. ^The analysis process that would be used in the multidisciplinary-feasible (MDF) optimization process is simulated using systems generated with the CASCADE methodology. ^Different convergence strategies are tested by collecting time and cost information over large numbers of such systems and using statistical techniques to compare the results. ^Primary emphasis is given to parallel strategies as might be used in a cooperative design environment. ^The results have demonstrated a profound impact of strategy choice on the cost and time of the convergence of a multidisciplinary analysis. ^They have also shown the importance of sequencing as used in some of the strategies. ^Results for the parallel strategies demonstrate an important time/cost trade-off. ^(Author)