Large Scale Generalized Reduced Gradient (LSGRG) Technique

The Large Scale Generalized Reduced Gradient (LSGRG) technique uses the generalized reduced gradient algorithm for solving constrained nonlinear optimization problems. The algorithm uses a search direction such that any active constraints remain precisely active for some small move in that direction.

The LSGRG algorithm operates by following the constraint boundaries throughout the design space one at a time. The order in which you specify the output constraints in the Optimization component editor may have an effect on the execution process. The output constraints you select first in the Optimization Component Editor will be operated on first by LSGRG. The final design point may be different depending on the order of constraint selection in the Optimization Component Editor, except in cases when the design space topology and the maximum number of iterations allow LSGRG to achieve full convergence to the same optimum design point.