Approximations play an important role in multidisciplinary design opti
mization by offering system behavior information at a relatively low c
ost. Most approximate optimization strategies are sequential, in which
an optimization of an approximate problem subject to design variable
move limits is iteratively repeated until convergence. The move limits
are imposed to restrict the optimization to regions of the design spa
ce in which the approximations provide meaningful information. To ensu
re convergence of the sequence of approximate optimizations to a Karus
h-Kuhn-Tucker solution a move-limit management strategy is required. I
n a companion paper, issues of move-limit management are reviewed and
a new adaptive strategy for move-limit management is developed (Wujek,
B, A., and Renaud, J, E., ''New Adaptive Move-Limit Management Strate
gy for Approximate Optimization, Part 1,'' AIAA Journal, Vol. 36, No.
10, 1998, pp, 1911-1921), With its basis in the provably convergent tr
ust region methodology, the trust region ratio approximation method (T
RAM) strategy utilizes available gradient information and employs a ba
cktracking process using various two-point approximation techniques to
provide a flexible move-limit adjustment factor. The TRAM strategy is
successfully implemented in application to several multidisciplinary
design optimization test problems. In addition, a comprehensive study
comparing the performance of the TRAM strategy to existing move-limit
strategies is conducted, Results indicate that application of the TRAM
strategy results in increased efficiency for approximate optimization
processes, These implementation studies highlight the ability of the
TRAM strategy to control the amount of approximation error and efficie
ntly manage the convergence to a Karush-Kuhn-Tucker solution.