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The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics) Anthony L. Peressini, Francis E. Sullivan, J.J. Uhl
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Van, ISBN 978-0-387-95012-9, 2000. The concepts, and many exercises at all levels of difficulty to test and strengthen understanding. The Mathematics of Nonlinear Programming--Peressini, A.L., Sullivan, F.E. €� filled with many useful examples and counterexamples that provide intuition to support the more formal theorems and proofs. An internationally renowned authority in mechanics and applied mathematics, Dr. Foundations of Optimization is an advanced graduate level text on the mathematical theory of optimization. Integral • A Practical Introduction--Carter, M., Brunt, B. Foundations of Optimization gives a detailed and rigorous treatment of the theory of optimization (unconstrained optimization, nonlinear programming, semi-infinite programming, etc.) in finite-dimensional spaces. UTM, 即Undergraduate Texts in Mathematics, 该系列比GTM系列出现得晚一些，也没有列序号，因此品种也略少一些，大部分是本科生数学教材，截止 2009年5月，出版的书名有（书目由ccddyy9提供）： .. Mathematical Modeling with Multidisciplinary Applications is an excellent book for courses on mathematical modeling and applied mathematics at the upper-undergraduate and graduate levels. The articles that comprise this distinguished annual volume for the Advances in Mechanics and Mathematics series have been written in honor of Gilbert Strang, a world renowned mathematician and exceptional person. Three techniques for finding a control strategy for optimal operation of a hydroelectric dam: using a nonlinear optimization algorithm, a nonlinear optimization algorithm with derivative functions, and quadratic programming. Lin's initial research in fluid mechanics and hydrodynamics stability and turbulence greatly influenced the field of fluid flow. To determine whether the wing design of a small passenger aircraft meets strength requirements, we derive analytical models of the loads and bending moments on the wing using the notebook interface in Symbolic Math Toolbox. The book offers several research technologies not yet well known among practitioners of discrete optimization, minimizes prerequisites for learning these methods, and provides a transition from linear discrete optimization to nonlinear discrete optimization.