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Reachable Sets of Dynamic Systems: Uncertainty, Sensitivity, and Complex Dynamics introduces differential inclusions, providing an overview as well as multiple examples of its interdisciplinary applications. The design of dynamic systems of any type is an important issue as is the influence of uncertainty in model parameters and model sensitivity. The possibility of calculating the reachable sets may be a powerful additional tool in such tasks. This book can help graduate students, researchers, and engineers working in the field of computer simulation and model building, in the calculation of reachable sets of dynamic models.
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In dynamic investment planning the time of investment is a significant issue. By simplifying the mathematical notation, the author of this book seeks to make control theory a practical tool that can be applied to the problem of timing. The book, first published in 1977, begins with an introduction to one important approach to control theory - dynamic programming. Then some of the relevant literature that deals with investment decision-making is reviewed. This is followed by a mathematically formulated planning model. The computational aspects of the model are discussed and a complete computer
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The profitability of power plant investments depends strongly on uncertain fuel and carbon prices. In this doctoral thesis, we combine fundamental electricity market models with stochastic dynamic programming to evaluate power plant investments under uncertainty. The application of interpolation-based stochastic dynamic programming and approximate dynamic programming allows us to consider a greater variety of stochastic fuel and carbon price scenarios compared to other approaches.
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Dynamic programming; sequential scientific management
Dynamic programming. --- Mathematical optimization --- Programming (Mathematics) --- Systems engineering
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Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. Because of these developments, interest in dynamic programming and Bayesian inference and their applications has greatly increased at all mathematical levels. The purpose of this book is to provide some applications of Bayesian optimization and dynamic programming.
Dynamic programming. --- Mathematical optimization --- Programming (Mathematics) --- Systems engineering --- Probability & statistics
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This book presents a unified theory of dynamic programming and Markov decision processes and its application to a major field of operations research and operations management: inventory control. Models are developed in discrete time as well as in continuous time. For continuous time, this book concentrates only on models of interest to inventory control. For discrete time, the focus is mainly on infinite horizon models. The book also covers the difference between impulse control and continuous control. Ergodic control is considered in the context of impulse control, and some simple rules curre
Dynamic programming. --- Inventory control --- Markov processes. --- Data processing.
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Nonserial dynamic programming
Dynamic programming. --- Dynamic programming --- Programming (Mathematics) --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Operations research --- Systems engineering
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Stochastic optimal control : the discrete time case
Stochastic processes --- Dynamic programming. --- Measure theory. --- Stochastic processes. --- Dynamic programming --- Measure theory --- Operations Research --- Civil & Environmental Engineering --- Engineering & Applied Sciences
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Design and develop high-performance, reusable, and maintainable applications using traditional and modern Julia patterns with this comprehensive guide Key Features Explore useful design patterns along with object-oriented programming in Julia 1.0 Implement macros and metaprogramming techniques to make your code faster, concise, and efficient Develop the skills necessary to implement design patterns for creating robust and maintainable applications Book Description Design patterns are fundamental techniques for developing reusable and maintainable code. They provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications. Starting with an overview of design patterns and best practices in application design, you'll learn about some of the most fundamental Julia features such as modules, data types, functions/interfaces, and metaprogramming. You'll then get to grips with the modern Julia design patterns for building large-scale applications with a focus on performance, reusability, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. You'll see how traditional object-oriented patterns can be implemented differently and more effectively in Julia. Finally, you'll explore various use cases and examples, such as how expert Julia developers use design patterns in their open source packages. By the end of this Julia programming book, you'll have learned methods to improve software design, extensibility, and reusability, and be able to use design patterns efficiently to overcome common challenges in software development. What you will learn Master the Julia language features that are key to developing large-scale software applications Discover design patterns to improve overall application architecture and design Develop reusable programs that are modular, extendable, performant, and easy to maintain Weigh up the pros and cons of using different design patterns for use cases Explore methods for transitioning from object-oriented programming to using equivalent or more advanced Julia techniques Who this book is for This book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale applications.
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The art and theory of dynamic programming
Dynamic programming. --- Mathematical optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mathematical optimization --- Programming (Mathematics) --- Systems engineering --- Dynamic programming --- Programmation dynamique --- ELSEVIER-B EPUB-LIV-FT
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