D-optimality criteria have been applied to construct locally optimal designs for a multiresponse, nonlinear model. Simulated annealing was used to perform the needed numerical optimization calculations, as this method can locate the global optimum of a function, and can efficiently handle constraints in the independent variables. The calculated optimal designs greatly reduce variances of model parameter estimates, compared to variances from previously used empirical designs. The effect of several design variables, including the number of design points and the number of responses, on the efficiency of the design was investigated, and designs for various subsets of parameters were also calculated. New directions for the design of.future experiments were suggested by this analysis.