Performance evaluation has been one of the most critical components in management. As production systems nowadays consist of a growing number of integrated and interacting processes, the interrelationship and dynamic among processes have create a major challenge in measuring system and process performance. Meanwhile, rapid information obsolescence has become a commonplace in today’s high-velocity environment. Managers therefore need to make process design decisions based on incomplete information regarding the future market. This thesis studies the above problems in the evaluation and design of complex production systems. Based on the widely used Data Envelopment Analysis models, we develop a generalized methodology to evaluate the dynamic efficiency of production networks. Our method evaluates both the supply network and its constituent firms in a systematic way. The evaluation result can help identify inefficiency in the network, which is important information for improving the network performance. Part II of the thesis covers multi-criteria process design methods developed for situations of different information availability. Our design approaches combine interdisciplinary techniques to facilitate efficient decision-making in situations with limited information and high uncertainty. As an illustration, we apply these approaches to project selection and resource allocation problems in a supply chain