Sequential Global Approximation in Non-Hierarchic System Decomposition and Optimization
John E. Renaud, Gary A. Gabriele · 1991
Abstract A procedure for the optimization of non-hierarchic systems by decomposition into reduced subspaces is presented. Sequential global approximation is proposed as a coordination procedure for subspace optimizations. The same objective function and cumulative constraints are imposed at each subspace. Non-local functions are approximated at the subspaces using global sensitivities. The method optimizes the subspace problems concurrently allowing for parallel processing. Following each sequence of concurrent subspace optimizations an approximation to the global problem is formed using design data accumulated during the subspace optimizations. The solution of the global approximation problem is used as the starting point for subsequent subspace optimizations in an iterative solution procedure. Preliminary studies on two engineering design examples illustrate the methods potential.