TWO APPROACHES TO MULTIDISCIPLINARY OPTIMIZATION PROBLEMS
ECCOMAS2000, Barselona, Spain, 2000.
This paper discusses two approaches to solve multidisciplinary optimization
problems regarding complex engineering systems. These approaches have
been developed in order to reduce computing time expenditures required
for solution of such problems.
The first approach is based on utilization of parallel computations not
only for object function computing, but also for an “internal” operation
of the algorithm that is parallelized. This allows for a significantly
higher acceleration of the problem solution process then a trivial usage
of parallel CPUs for optimization criteria calculation. The results of
numerical testing for the new algorithm are presented.
The second approach consists of using multiple fidelity (multilevel)
analysis algorithms. The results of a reallife stochastic multiobjective
optimization problem solution are presented. The usage of multilevel approach
for such optimization problems results in a significant reduction of computing
time.
