Convex Optimization & Euclidean Distance Geometry (repost)
Jon Dattorro, "Convex Optimization & Euclidean Distance Geometry"
English | 2008-03-13 | ISBN: 0615193684 | 812 pages | PDF | 9.6 mb
English | 2008-03-13 | ISBN: 0615193684 | 812 pages | PDF | 9.6 mb
Convex Analysis is the calculus of inequalities while Convex Optimization is its application. Analysis is inherently the domain of the mathematician while Optimization belongs to the engineer. In layman's terms, the mathematical science of Optimization is the study of how to make a good choice when confronted with conflicting requirements.
The qualifier Convex means: when an optimal solution is found, then it is guaranteed to be a best solution; there is no better choice. Any Convex Optimization problem has geometric interpretation. Conversely, recent advances in geometry and in graph theory hold Convex Optimization within their proofs' core. This book is about Convex Optimization, convex geometry (with particular attention to distance geometry), and nonconvex, combinatorial, and geometrical problems that can be relaxed or transformed into convex problems. A virtual flood of new applications follows by epiphany that many problems, presumed nonconvex, can be so transformed. International Edition II.