In this paper we consider the problem of automatically determining optimal drawbead sizes and blankholder forces when designing draw dies for stamped parts. A network of software agents, each implementing a different numerical optimization technique, was used in combination with metal forming simulation software to optimize process variables. Three test cases were used of varying complexity from a rectangular cup to the NUMISHEET’99 automobile front door panel simulation benchmark. It was found that the performance of each agent (and optimization technique) depended strongly on the complexity of the problem. More interestingly, for a given amount of computational effort, a network of collaborating agents using different optimization techniques always outperformed agents using a single technique in terms of both the best solution found and in the variance of the collection of best solutions.