Robust design employing a genetic algorithm

Abstract

The minimization of variability in a key design feature or performance measure, in the presence of variability in the realized values of design parameters, is discussed and an analytic solution for quadratic performance measures is provided. Solutions are based on the determination of optimum nominal (or design point) values for the design parameters, subject to constraints in the form of a given nominal performance at the design point and limits on the nominal values of the design parameters, which preserve the design concept. The more general, numerical, problem solution is addressed and a previously described deterministic procedure which generated multiple local optima is improved by the replacement of a simplex search method with a sophisticated genetic algorithm which, with suitable parameter values and choice of Lagrange multiplier, converges only to the required global minimum within the specified design parameter limits. Further improvements are discussed. Copyright © 2000 John Wiley & Sons, Ltd.

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