Constructing exact d-optimal experimental designs by simulated annealing

Exact optimal designs have generally been constructed using a finite design space and various exchange algorithms, which are subject to premature convergence. Branch-and-bound methods guarantee optimal designs, but are only computationally feasible for small problems. We apply the generalized simulated annealing algorithm to the construction of exact optimal designs, and evaluate its effectiveness on both finite and continuous design spaces.