This up-to-date reference offers valuable theoretical, algorithmic, and computational guidelines for solving the most frequently encountered linear-quadratic optimization problems - providing an overview of recent advances in control and systems theory, numerical linear algebra, numerical optimization, scientific computations, and software engineering. Examining state-of-the-art linear algebra algorithms and associated software, Algorithms for Linear-Quadratic Optimization presents algorithms in a concise, informal language that facilitates computer implementation...discusses the mathematical description, applicability, and limitations of particular solvers...summarizes numerical comparisons of various algorithms...highlights topics of current interest, including H[subscript infinity] and H[subscript 2] optimization, defect correction, and Schur and generalized-Schur vector methods...emphasizes structure-preserving techniques...contains many worked examples based on industrial models...covers fundamental issues in control and systems theory such as regulator and estimator design, state estimation, and robust control...and more. Furnishing valuable references to key sources in the literature, Algorithms for Linear-Quadratic Optimization is an incomparable reference for applied and industrial mathematicians, control engineers, computer programmers, electrical and electronics engineers, systems analysts, operations research specialists, researchers in automatic control and dynamic optimization, and graduate students in these disciplines.