Products related to Optimization:
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Basic Concepts of Global Optimization
This textbook is an introduction to global optimization, which treats mathematical facts stringently on the one hand, but also motivates them in great detail and illustrates them with 80 figures.The book is therefore not only aimed at mathematicians, but also at natural scientists, engineers and economists who want to understand and apply mathematically sound methods in their field. With almost two hundred pages, the book provides enough choices to use it as a basis for differently designed lectures on global optimization.The detailed treatment of the global solvability of optimization problems under application-relevant conditions sets a new accent that enriches the stock of previous textbooks on optimization.Using the theory and algorithms of smooth convex optimization, the book illustrates that the global solution of a class of optimization problems frequently encountered in practice is efficiently possible, while for the more difficult-to-handle non-convex problems itdevelops in detail the ideas of branch-and-bound methods. This book is the English translation of the 2nd edition of “Grundzüge der Globalen Optimierung” (Springer, 2021) written in German.The translation was done with the help of artificial intelligence.A subsequent revision was performed by the author to further refine the work and to ensure that the translation is appropriate concerning content and scientific correctness.It may, however, read stylistically different from a conventional translation.
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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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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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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 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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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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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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Women in Mass Communication : Diversity, Equity, and Inclusion
This fourth edition of Women in Mass Communication addresses the myriad changes in media and mass communication disciplines in relation to women over the last five decades. This volume traces the history of diversity, equity, and inclusion for women in media, enabling greater understanding of global discourses and inequities, exploring transnational feminism, offering criticism of underlying structures, and calling for meaningful changes to media systems.With particular emphasis on educational and professional approaches to media communication, the book brings together a wide variety of specific topics and connects them through an intersectional feminist lens that values diversity, equity, and inclusion while exposing global systemic misogyny.The volume features 23 authors with a variety of backgrounds and perspectives from Australia, Germany, Ghana, Kenya, Korea, New Zealand, Saudi Arabia, United Arab Emirates, United Kingdom, and the United States.This fourth edition focuses on marginalization practices—race, ethnicity, LGBTQ+, social class, and in multiple societies—providing insight into identity and difference in a global context.An important text for students and scholars examining gender in relation to mass communication, media studies, and journalism, as well as those exploring wider issues of diversity, equity, and inclusion within these disciplines.
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Diversity and Inclusion in Global Higher Education
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Engineering Optimization 2014
Modern engineering processes and tasks are highly complex, multi- and interdisciplinary, requiring the cooperative effort of different specialists from engineering, mathematics, computer science and even social sciences.Optimization methodologies are fundamental instruments to tackle this complexity, giving the possibility to unite synergistically team members’ inputs and thus decisively contribute to solving new engineering technological challenges.With this context in mind, the main goal of Engineering Optimization 2014 is to unite engineers, applied mathematicians, computer and other applied scientists working on research, development and practical application of optimization methods applied to all engineering disciplines, in a common scientific forum to present, analyze and discuss the latest developments in this area. Engineering Optimization 2014 contains the edited papers presented at the 4th International Conference on Engineering Optimization (ENGOPT2014, Lisbon, Portugal, 8-11 September 2014).ENGOPT2014 is the fourth edition of the biennial “International Conference on Engineering Optimization”.The first conference took place in 2008 in Rio de Janeiro, the second in Lisbon in 2010 and the third in Rio de Janeiro in 2012.?The contributing papers are organized around the following major themes:?- Numerical Optimization Techniques- Design Optimization and Inverse Problems- Effi cient Analysis and Reanalysis Techniques- Sensitivity Analysis- Industrial Applications- Topology Optimization For Structural Static and Dynamic Failures- Optimization in Oil and Gas Industries- New Advances in Derivative-Free Optimization Methods for Engineering Optimization- Optimization Methods in Biomechanics and Biomedical Engineering- Optimization of Laminated Composite Materials- Inverse Problems in EngineeringEngineering Optimization 2014 will be of great interest to engineers and academics in engineering, mathematics and computer science.
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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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What is the difference between intercultural and multicultural?
Intercultural refers to interactions and communication between people from different cultures, focusing on the exchange and understanding of different cultural perspectives. It emphasizes the process of learning and adapting to different cultural norms and values. On the other hand, multicultural refers to the coexistence of multiple cultures within a society, emphasizing the diversity and variety of cultural backgrounds present in a given community. It focuses on the recognition and celebration of different cultural traditions and identities. In summary, intercultural emphasizes the interaction and understanding between cultures, while multicultural emphasizes the coexistence and diversity of cultures within a society.
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What does self-optimization mean?
Self-optimization refers to the process of improving oneself in various aspects such as physical, mental, emotional, and spiritual well-being. It involves setting personal goals, identifying areas for improvement, and taking deliberate actions to enhance one's overall quality of life. Self-optimization also involves self-reflection, self-awareness, and continuous learning to achieve personal growth and fulfillment. It is a proactive approach to self-improvement and self-care, aiming to maximize one's potential and live a more balanced and fulfilling life.
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