Products related to Optimization:
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Optimization in Economic Theory
* This is the new edition of a popular student textbook.The first edition was well-received. The author has made revisions and additions to enhance the book's usefulness without destroying its distinctive character as a lucid, thorough, and readable text.It gives a broad treatment of optimization methods, building on simple economic theory and elementary linear algebra and calculus, and reinforcing each new mathematical idea by relating it to its economics application.
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Optimization Methods in Finance
Optimization methods play a central role in financial modeling.This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance.It discusses some classical mean-variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes.Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance.This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering.The second edition includes new examples and exercises as well as a more detailed discussion of mean-variance optimization, multi-period models, and additional material to highlight the relevance to finance.
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Optimization in Chemical Engineering
Optimization is used to determine the most appropriate value of variables under given conditions.The primary focus of using optimisation techniques is to measure the maximum or minimum value of a function depending on the circumstances.This book discusses problem formulation and problem solving with the help of algorithms such as secant method, quasi-Newton method, linear programming and dynamic programming.It also explains important chemical processes such as fluid flow systems, heat exchangers, chemical reactors and distillation systems using solved examples.The book begins by explaining the fundamental concepts followed by an elucidation of various modern techniques including trust-region methods, Levenberg-Marquardt algorithms, stochastic optimization, simulated annealing and statistical optimization.It studies the multi-objective optimization technique and its applications in chemical engineering and also discusses the theory and applications of various optimization software tools including LINGO, MATLAB, MINITAB and GAMS.
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Convex Optimization
Convex optimization problems arise frequently in many different fields.This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency.The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems.Duality and approximation techniques are then covered, as are statistical estimation techniques.Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods.The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them.It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.
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How can I restore optimization in Avira Game Booster?
To restore optimization in Avira Game Booster, you can try the following steps: 1. Make sure that Avira Game Booster is running in the background while you are playing games. 2. Check if there are any updates available for Avira Game Booster and install them. 3. Restart your computer to refresh the system and ensure that Avira Game Booster is working properly. 4. If the issue persists, you can try uninstalling and then reinstalling Avira Game Booster to reset its settings and restore optimization.
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How can I restore the optimization in Avira Game Booster?
To restore the optimization in Avira Game Booster, you can try the following steps: 1. Open the Avira Game Booster application and navigate to the settings or options menu. 2. Look for an option to reset or restore the optimization settings to their default values. 3. If there is no specific option for restoring the optimization, you can try uninstalling and reinstalling the Avira Game Booster application to reset the settings. 4. Once the application is reinstalled, you can reconfigure the optimization settings according to your preferences.
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What is price optimization?
Price optimization is the process of using data and analytics to determine the most effective pricing strategy for a product or service. It involves analyzing factors such as market demand, competitor pricing, and customer behavior to set prices that maximize revenue and profit. By continuously adjusting prices based on these insights, businesses can find the optimal balance between attracting customers and maximizing profitability. Price optimization helps businesses stay competitive in the market and adapt to changing conditions to achieve their financial goals.
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What is linear optimization?
Linear optimization, also known as linear programming, is a mathematical method for determining the best outcome in a given mathematical model for a given set of requirements. It involves maximizing or minimizing a linear objective function, subject to a set of linear equality and inequality constraints. Linear optimization is widely used in various fields such as economics, engineering, and business to optimize resource allocation, production planning, and decision-making processes. It provides a systematic and efficient approach to solving complex problems with multiple variables and constraints.
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Robust Optimization
Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology.Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject.Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution.The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems.The theory is supported by numerous examples and computational illustrations.An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
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Numerical Optimization
Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization.It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. For this new edition the book has been thoroughly updated throughout.There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience.It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business.It also serves as a handbook for researchers and practitioners in the field.The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side. There is a selected solutions manual for instructors for the new edition.
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Bayesian Optimization
Bayesian optimization is a methodology for optimizing expensive objective functions that has proven success in the sciences, engineering, and beyond.This timely text provides a self-contained and comprehensive introduction to the subject, starting from scratch and carefully developing all the key ideas along the way.This bottom-up approach illuminates unifying themes in the design of Bayesian optimization algorithms and builds a solid theoretical foundation for approaching novel situations.The core of the book is divided into three main parts, covering theoretical and practical aspects of Gaussian process modeling, the Bayesian approach to sequential decision making, and the realization and computation of practical and effective optimization policies.Following this foundational material, the book provides an overview of theoretical convergence results, a survey of notable extensions, a comprehensive history of Bayesian optimization, and an extensive annotated bibliography of applications.
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Optimization Algorithms
Solve design, planning, and control problems using modern machine learning and AI techniques. In Optimization Algorithms: AI techniques for design, planning, and control problems you will learn: Machine learning methods for search and optimization problemsThe core concepts of search and optimizationDeterministic and stochastic optimization techniquesGraph search algorithmsNature-inspired search and optimization algorithmsEfficient trade-offs between search space exploration and exploitationState-of-the-art Python libraries for search and optimization About the technology: Search and optimization algorithms are powerful tools that can help practitioners find optimal or near-optimal solutions to a wide range of design, planning and control problems.When you open a route planning app, call for a rideshare, or schedule a hospital appointment, an AI algorithm works behind the scenes to make sure you get an optimized result.This guide reveals the classical and modern algorithms behind these services.
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What is upstream optimization?
Upstream optimization refers to the process of identifying and addressing issues at the beginning of a production or supply chain to improve overall efficiency and effectiveness. By focusing on optimizing processes, materials, and resources at the upstream stage, companies can prevent problems from occurring downstream, leading to cost savings, improved quality, and increased productivity. This proactive approach helps organizations streamline their operations and enhance their competitive advantage in the market.
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Is map optimization harmful?
No, map optimization is not harmful. In fact, it is beneficial for improving the user experience, reducing load times, and increasing website performance. Properly optimizing maps can help websites load faster and provide a better overall experience for users.
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What is mathematical optimization?
Mathematical optimization is the process of finding the best solution to a problem from a set of possible solutions. It involves maximizing or minimizing a certain objective function while satisfying a set of constraints. This can be applied to a wide range of fields, including engineering, economics, and computer science, to help make better decisions and improve efficiency. Optimization problems can be solved using various mathematical techniques such as linear programming, nonlinear programming, and integer programming.
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What is optimization 3?
Optimization 3 refers to the process of maximizing or improving the efficiency and effectiveness of a system, process, or strategy. It involves identifying areas for improvement, setting specific goals, and implementing changes to achieve the best possible outcome. Optimization 3 often involves using data analysis, mathematical modeling, and advanced algorithms to make informed decisions and drive continuous improvement. This approach is commonly used in various fields such as engineering, business, and technology to enhance performance and achieve better results.
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