Asymptotically D-Optimal Design of Mixture Experiment with Complex Constraints

It is difficult to get an accurate optimum design when the experimental design area is very irregular under complex constraints. This paper constructs a random search algorithm for mixture experiments designed (MDRS). Firstly, generating an initial points set in areas with complex constraints by the Monte-Carlo method, then use MDRS algorithm iterative to approximate optimum set. By way of example verification, this method is effective. It can be used as a standard measure of other designs, that is the only effective when given superior to other designs approximate optimal solution.