Title: MPCCs in Integrated Design and Control � Formulation, Solution and Challenges

Mathematical programs with complementarity constraints (MPCCs) arise in a number of areas including game theory, economics, transportation and engineering applications. Discouraging numerical experience in solving MPCCs as NLPs led to the development of specialized algorithms for problems of this type. However, recent developments, supported by theoretical analysis, have shown that MPCCs can be reliably solved as NLPs with relatively minor modification to the problem formulation and/or optimization algorithm. In this presentation, we focus on MPCCs that arise in integrated design and control. Problem characteristics include the presence of differential-algebraic equation constraints, model discontinuities, and in some problem classes, a bilevel optimization structure. The formulation of these problems as MPCCs will be discussed, as well as our computational experience with this approach. Some comparisons with an alternative mixed-integer programming approach will also be presented. Case studies in process design and operations will be included, and research challenges identified.