The first book to provide a comprehensive treatment integrating finite-time thermodynamics and optimal control, giving an overview of important breakthroughs in the last 20 years.<br> <br> It presents a survey of the optimization technique, including the basics of optimal control theory, and the principal thermodynamic concepts and equations. In addition, it covers the solutions of a variety of finite-time thermodynamic problems, including coverage of their potential applications for the design of real technological processes, such as:<br> <br> * heat-exchange systems<br> <br> * mass transfer and separation processes<br> <br> * commodity exchange as a finite-time thermodynamic process<br> <br> * heat-driven mechanical processes with one or several reservoirs.<br> <br> This is a key resource for chemical and mechanical engineers involved in power systems and process engineering. Researchers in theoretical, physical and industrial chemistry in academia and in industry will also welcome this book for the fresh perspectives that offer new ways to design and analyze a wide variety of processes.
In 1984, N. Karmarkar published a seminal paper on algorithmic linear programming. During the subsequent decade, it stimulated a huge outpouring of new algorithmic results by researchers world-wide in many areas of mathematical programming and numerical computation. This book gives an overview of the resulting, dramatic reorganization that has occurred in one of these areas: algorithmic differentiable optimization and equation-solving, or, more simply, algorithmic differentiable programming. The book is aimed at readers familiar with advanced calculus, numerical analysis, in particular numerical linear algebra, the theory and algorithms of linear and nonlinear programming, and the fundamentals of computer science, in particular, computer programming and the basic models of computation and complexity theory. J.L. Nazareth is a Professor in the Department of Pure and Applied Mathematics at Washington State University. He is the author of two books previously published by Springer-Verlag, DLP and Extensions: An Optimization Model and Decision Support System (2001) and The Newton-Cauchy Framework: A Unified Approach to Unconstrained Nonlinear Minimization (1994).
The book is intended for people (graduates, researchers, but also undergraduates with a good mathematical background) involved in the study of (static) optimization problems (in finite-dimensional spaces). It contains a lot of material, from basic tools of convex analysis to optimality conditions for smooth optimization problems, for non smooth optimization problems and for vector optimization problems.
True to the nature of the Gedenkschrift, this commemorative publication celebrates the work of sociologist Dr. William Freudenburg, one of the founding editors of RSPPP and Dehlsen Professor, University of California, Santa Barbara. Chapters include personal reminiscences as well as research that reflect and build on Dr. Freudenburgs theories including recreancy, bureaucratic slippage, his research in environmental disasters, climate change natural resources, technological risk and Scientific Certainty Argumentation Method (SCAM). Government transparency, power and control are also among the topics discussed.
A presentation of general results for discussing local optimality and computation of the expansion of value function and approximate solution of optimization problems, followed by their application to various fields, from physics to economics. The book is thus an opportunity for popularizing these techniques among researchers involved in other sciences, including users of optimization in a wide sense, in mechanics, physics, statistics, finance and economics. Of use to research professionals, including graduate students at an advanced level.
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