Many engineering and scientific problems in design, control, and parameter estimation can be formulated as optimization problems that are governed by partial differential equations (PDEs). The complexities of the PDEs - and the requirement for rapid solution - pose significant difficulties. A particularly challenging class of PDE-constrained optimization problems is characterized by the need for real-time solution, i.e., in time scales that are sufficiently rapid to support simulation-based decision making. Real-Time PDE-Constrained Optimization, the first book devoted to real-time optimization for systems governed by PDEs, focuses on new formulations, methods, and algorithms needed to facilitate real-time, PDE-constrained optimization. In addition to presenting state-of-the-art algorithms and formulations, the text illustrates these algorithms with a diverse set of applications that includes problems in the areas of aerodynamics, biology, fluid dynamics, medicine, chemical processes, homeland security, and structural dynamics.

About the Authors

Lorenz T. Biegler is the Bayer Professor of Chemical Engineering at Carnegie Mellon University.

Omar Ghattas is the John A. and Katherine G. Jackson Chair in Computational Geosciences at the University of Texas at Austin.

Matthias Heinkenschloss is Professor of Computational and Applied Mathematics at Rice University.

David E. Keyes is the Fu Foundation Professor of Applied Mathematics at Columbia University.

Bart van Bloemen Waanders is Principal Member of the Technical Staff at Sandia National Laboratories.

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