We consider the modeling and optimization of dynamic hybrid systems. Such systems occur widely in nature (particular in biological, chemical and mechanical applications) and are also essential components of economic planning models. For optimization formulations, these discontinuous decisions are represented as binary variables, leading to mixed integer nonlinear programs (MINLPs), or through complementarity relations, leading to mathematical programs with complementarity constraints (MPCC). Our research will consider both MINLP and MPCC problems over a broad set of application domains and we intend to develop new optimization strategies that combine MPCC and MINLP algorithms within a single strategy. These research results will be applied to broad set of applications including systems biology and drug design, planning and scheduling models for enterprise wide optimization, applications of hybrid models in mechanical and process engineering systems. Finally, these results of this research will allow consideration of challenging dynamic hybrid systems too large to be considered with existing optimization strategies.

Collaborators

• L. Biegler, University of Carnegie Mellon, Department of Chemical Engineering (Coordinator)
• B. Karasözen, Department of Mathematics & Institute of Applied Mathematics, METU (Coordinator)
• M. Türkay, Koç University, Department of Industrial Engineering
• H. Oktem, Institute of Applied Mathematics, METU
• A. Tezel, Department of Mathematics, METU

Funded by TUBITAK-NSF 2005-2008, Scientific and Technical Research Council of Turkey