Products related to Optimization:
-
Predictive Analytics : Modeling and Optimization
Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence.This book provides the most recent advances in the field along with case studies and real-world examples.It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management.It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples.The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management.Students taking courses in these areas will also find this book of interest.
Price: 135.00 £ | Shipping*: 0.00 £ -
Analytics and Optimization for Renewable Energy Integration
The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration.The first part presents mathematical theories of stochastic mathematics; the second presents modeling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation.It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.
Price: 45.99 £ | Shipping*: 0.00 £ -
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.
Price: 84.99 £ | Shipping*: 0.00 £ -
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.
Price: 92.00 £ | Shipping*: 0.00 £
-
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.
-
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.
-
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.
-
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.
Similar search terms for Optimization:
-
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.
Price: 64.99 £ | Shipping*: 0.00 £ -
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.
Price: 44.99 £ | Shipping*: 0.00 £ -
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.
Price: 69.99 £ | Shipping*: 0.00 £ -
Intelligent Computing and Optimization for Sustainable Development
This book presents insights into how Intelligent Computing and Optimization techniques can be used to attain the goals of Sustainable Development.It provides a comprehensive overview of the latest breakthroughs and recent developments in sustainable, intelligent computing technologies, applications, and optimization techniques across various industries, including business process management, manufacturing, financial sector, agriculture, financial sector, supply chain management, and healthcare.It focuses on computational intelligent techniques and optimization techniques to provide sustainable solutions to many problems.Features: • Provides insights into the theory, implementation, and application of computational intelligence techniques in many industries. • Includes industry practitioner perspectives and case studies for a better understanding of sustainable solutions. • Highlights the role of intelligent computing and optimization as key technologies in decision-making processes and in providing cutting-edge solutions to real-world problems. • Addresses the challenges and limitations of computational approaches in sustainability, such as data availability, model uncertainty, and computational complexity, while also discusses emerging opportunities and future directions in the field.This book will be useful for professionals and scholars looking for up-to-date research on cutting-edge perspectives in the field of computational intelligent and optimization techniques in the areas of agriculture, industry, financial sector, business automation, renewable energy, optimization, and smart cities.
Price: 140.00 £ | Shipping*: 0.00 £
-
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.
-
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.
-
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.
-
Can you explain 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. The objective function represents the quantity to be optimized, while the constraints represent the limitations or restrictions on the decision variables. Linear optimization is widely used in various fields such as economics, engineering, and business to make efficient use of resources and to optimize decision-making processes.
* All prices are inclusive of VAT and, if applicable, plus shipping costs. The offer information is based on the details provided by the respective shop and is updated through automated processes. Real-time updates do not occur, so deviations can occur in individual cases.