Deterministic Global Optimization in Systems Engineering

Princeton University, Princeton NJ

Investigators

Abstract

ABSTRACT PI: Christodoulos A. Floudas Institution: Princeton University Proposal Number: 0002777 The primary objective of this research is to develop theoretical, algorithmic and computational techniques for global optimization problems that arise in a variety of chemical engineering design and synthesis problems, as well as NMR structure refinement problems that arise in computational chemistry and biology. These methods will complement efforts in the mathematical modeling of chemical process systems and aid the search in the design of molecules, peptides, and proteins. The PI plans to investigate (1) the extension of his global optimization framework, aBB, to differential algebraic models that arise in parameter estimation and control; (2) the development of a new global optimization-based approach for general bilevel and multilevel nonlinear models that arise in the design under uncertainty, and the interaction of process synthesis, desing and operations; (3) the development of novel approaches for convex and nonconvex mixed integer nonlinear optimization models that arise in process synthesis; (4) the structure prediction of peptides with the presence of sparse restraints provided by NMR experiments; and (5) development of global optimization tools and the study of a distributed computing framework for the aBB global optimization approach for (1) - (4) above. These will be applied to several classes of chemical process synthesis, design, control and computational chemistry problems. The innovative features of this work consist of: (a) new global optimization methods for models with differential and algebraic constraints; (b) new global optimization approaches for bilevel and multilevel nonlinear models; (c) new approaches that combine strong cutting planes and branch and bound principles for mixed integer nonlinear optimization problems; (d) new methods for the determination of the structure of peptides and proteins through the NMR restraints that arise in computational chemistry and biology; and (e) sequential and distributed computational tools for all tasks of the planned work.