Introduction to Dynamic Programming (eBook, PDF)
International Series in Modern Applied Mathematics and Computer Science, Volume 1
Redaktion: Rodin, E. Y.
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Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Mark...
Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.
Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Markov processes, chemical engineering, optimal control theory, calculus of variations, and economics. This book discusses as well the approach to problem solving that is typical of dynamic programming. The final chapter deals with a number of actual applications of dynamic programming to practical problems.
This book is a valuable resource for .graduate level students of mathematics, economics, statistics, business, operations research, industrial engineering, or other engineering fields.
Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Markov processes, chemical engineering, optimal control theory, calculus of variations, and economics. This book discusses as well the approach to problem solving that is typical of dynamic programming. The final chapter deals with a number of actual applications of dynamic programming to practical problems.
This book is a valuable resource for .graduate level students of mathematics, economics, statistics, business, operations research, industrial engineering, or other engineering fields.
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