(264d) Mpec Strategies for Optimization of Chemical Process Dynamics

With the development and widespread use of large-scale nonlinear programming (NLP) tools for process optimization, there has been an associated application of NLP formulations with complementarity constraints in order to represent discrete decisions. Also known as Mathematical Programs with Equilibrium Constraints (MPECs), these formulations can be used to model certain classes of discrete events and can be more efficient than a mixed integer formulation. In this talk, we consider MPEC formulations and solution strategies for chemical engineering applications, particularly for a dynamic gas pipeline system. The results illustrate the effectiveness of MPEC strategies as well as some novel operating strategies for pipeline networks.