Problem Formulation for Multidisciplinary Optimization

This paper is concerned with the optimization of systems of coupled simulations. In computational engineering, this frequently is called multidisciplinary (design) optimization, or MDO. We present an expository introduction to MDO for optimization researchers. We believe the optimization community has much to contribute to this important class of computational engineering problems. In addition, this paper presents a new abstraction for multidisciplinary analysis and design problems as well as new decomposition formulations for these problems. Furthermore, the "individual discipline feasible" (IDF) approaches suggested here make use of existing specialized simulation analysis codes, and they introduce significant opportunities for coarse-grained computational parallelism particularly well-suited to heterogeneous computing environments. The key issue in the three fundamental approaches to MDO formulation discussed here is the kind of feasibility that must be maintained at each optimizati..