The proposed approach is based on three stages which (1) use neural networks for constructing a response

function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating

overall performance of a specific factor combination, and (3) use a genetic algorithm to optimize

parameter design. Effectiveness of the proposed approach is illustrated with a simulated example. Analysis

results reveal that the approach has higher performance than the traditional experimental design.