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Author: Mohammad Fathi Publisher: Springer ISBN: 3030053091 Category : Technology & Engineering Languages : en Pages : 174
Book Description
This textbook provides students, researchers, and engineers in the area of electrical engineering with advanced mathematical optimization methods. Presented in a readable format, this book highlights fundamental concepts of advanced optimization used in electrical engineering. Chapters provide a collection that ranges from simple yet important concepts such as unconstrained optimization to highly advanced topics such as linear matrix inequalities and artificial intelligence-based optimization methodologies. The reader is motivated to engage with the content via numerous application examples of optimization in the area of electrical engineering. The book begins with an extended review of linear algebra that is a prerequisite to mathematical optimization. It then precedes with unconstrained optimization, convex programming, duality, linear matrix inequality, and intelligent optimization methods. This book can be used as the main text in courses such as Engineering Optimization, Convex Engineering Optimization, Advanced Engineering Mathematics and Robust Optimization and will be useful for practicing design engineers in electrical engineering fields. Author provided cases studies and worked examples are included for student and instructor use.
Author: Mohammad Fathi Publisher: Springer ISBN: 3030053091 Category : Technology & Engineering Languages : en Pages : 174
Book Description
This textbook provides students, researchers, and engineers in the area of electrical engineering with advanced mathematical optimization methods. Presented in a readable format, this book highlights fundamental concepts of advanced optimization used in electrical engineering. Chapters provide a collection that ranges from simple yet important concepts such as unconstrained optimization to highly advanced topics such as linear matrix inequalities and artificial intelligence-based optimization methodologies. The reader is motivated to engage with the content via numerous application examples of optimization in the area of electrical engineering. The book begins with an extended review of linear algebra that is a prerequisite to mathematical optimization. It then precedes with unconstrained optimization, convex programming, duality, linear matrix inequality, and intelligent optimization methods. This book can be used as the main text in courses such as Engineering Optimization, Convex Engineering Optimization, Advanced Engineering Mathematics and Robust Optimization and will be useful for practicing design engineers in electrical engineering fields. Author provided cases studies and worked examples are included for student and instructor use.
Author: Navid Razmjooy Publisher: Springer Nature ISBN: 3030566897 Category : Technology & Engineering Languages : en Pages : 311
Book Description
The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.
Author: Mohamed Bakr Publisher: IET ISBN: 1849195439 Category : Computers Languages : en Pages : 325
Book Description
Nonlinear Optimization in Electrical Engineering with Applications in MATLAB® provides an introductory course on nonlinear optimization in electrical engineering, with a focus on applications such as the design of electric, microwave, and photonic circuits, wireless communications, and digital filter design.
Author: Navid Razmjooy Publisher: Springer Nature ISBN: 3031426851 Category : Technology & Engineering Languages : en Pages : 491
Book Description
This book discusses different methods of modifying the original metaheuristics and their application in computer and electrical engineering. As the race to develop advanced technology accelerates, a new era of "metaheuristics" has emerged. Through researched-based techniques and collaborative problem-solving, this book helps engineers to find efficient solutions to their engineering challenges. With the help of an expert guide and the collective knowledge of the engineering community, this comprehensive guide shows readers how to use machine learning and other AI techniques to reinvent smart engineering. From understanding the fundamentals to mastering the latest metaheuristics models, this guide provides with the skills and knowledge that need to stay ahead in the technology race. In the previous volume, authors focused on the application of original metaheuristics on electrical and computer sciences. This volume learns how AI and modified metaheuristics can be used to optimize algorithms and create more efficient electrical engineering designs. It gets insights on how data can be effectively processed and discover new techniques for creating sophisticated automation systems. It maximizes the potential of readers’ computer and electrical engineering projects with powerful metaheuristics and optimization techniques.
Author: Kaushik Kumar Publisher: John Wiley & Sons ISBN: 1119644615 Category : Technology & Engineering Languages : en Pages : 150
Book Description
Optimization is central to any problem involving decision-making in engineering. Optimization theory and methods deal with selecting the best option regarding the given objective function or performance index. New algorithmic and theoretical techniques have been developed for this purpose, and have rapidly diffused into other disciplines. As a result, our knowledge of all aspects of the field has grown even more profound. In Optimization for Engineering Problems, eminent researchers in the field present the latest knowledge and techniques on the subject of optimization in engineering. Whereas the majority of work in this area focuses on other applications, this book applies advanced and algorithm-based optimization techniques specifically to problems in engineering.
Author: Simone Göttlich Publisher: Springer Nature ISBN: 3030627322 Category : Technology & Engineering Languages : en Pages : 333
Book Description
This edited monograph offers a summary of future mathematical methods supporting the recent energy sector transformation. It collects current contributions on innovative methods and algorithms. Advances in mathematical techniques and scientific computing methods are presented centering around economic aspects, technical realization and large-scale networks. Over twenty authors focus on the mathematical modeling of such future systems with careful analysis of desired properties and arising scales. Numerical investigations include efficient methods for the simulation of possibly large-scale interconnected energy systems and modern techniques for optimization purposes to guarantee stable and reliable future operations. The target audience comprises research scientists, researchers in the R&D field, and practitioners. Since the book highlights possible future research directions, graduate students in the field of mathematical modeling or electrical engineering may also benefit strongly.
Author: A. Kaveh Publisher: Springer ISBN: 331948012X Category : Technology & Engineering Languages : en Pages : 373
Book Description
The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering.
Author: James A. Momoh Publisher: CRC Press ISBN: 1420065874 Category : Technology & Engineering Languages : en Pages : 602
Book Description
As the demand for energy continues to grow, optimization has risen to the forefront of power engineering research and development. Continuing in the bestselling tradition of the first edition, Electric Power System Applications of Optimization, Second Edition presents the theoretical background of optimization from a practical power system point of view, exploring advanced techniques, new directions, and continuous application problems. The book provides both the analytical formulation of optimization and various algorithmic issues that arise in the application of various methods in power system planning and operation. The second edition adds new functions involving market programs, pricing, reliability, and advances in intelligent systems with implemented algorithms and illustrative examples. It describes recent developments in the field of Adaptive Critics Design and practical applications of approximate dynamic programming. To round out the coverage, the final chapter combines fundamental theories and theorems from functional optimization, optimal control, and dynamic programming to explain new Adaptive Dynamic Programming concepts and variants. With its one-of-a-kind integration of cornerstone optimization principles with application examples, this second edition propels power engineers to new discoveries in providing optimal supplies of energy.
Author: Xu Andy Sun Publisher: Springer Nature ISBN: 3030851281 Category : Business & Economics Languages : en Pages : 337
Book Description
This book covers robust optimization theory and applications in the electricity sector. The advantage of robust optimization with respect to other methodologies for decision making under uncertainty are first discussed. Then, the robust optimization theory is covered in a friendly and tutorial manner. Finally, a number of insightful short- and long-term applications pertaining to the electricity sector are considered. Specifically, the book includes: robust set characterization, robust optimization, adaptive robust optimization, hybrid robust-stochastic optimization, applications to short- and medium-term operations problems in the electricity sector, and applications to long-term investment problems in the electricity sector. Each chapter contains end-of-chapter problems, making it suitable for use as a text. The purpose of the book is to provide a self-contained overview of robust optimization techniques for decision making under uncertainty in the electricity sector. The targeted audience includes industrial and power engineering students and practitioners in energy fields. The young field of robust optimization is reaching maturity in many respects. It is also useful for practitioners, as it provides a number of electricity industry applications described up to working algorithms (in JuliaOpt).
Author: Mohammad Kiani-Moghaddam Publisher: Springer ISBN: 3030120449 Category : Technology & Engineering Languages : en Pages : 727
Book Description
In today’s world, with an increase in the breadth and scope of real-world engineering optimization problems as well as with the advent of big data, improving the performance and efficiency of algorithms for solving such problems has become an indispensable need for specialists and researchers. In contrast to conventional books in the field that employ traditional single-stage computational, single-dimensional, and single-homogeneous optimization algorithms, this book addresses multiple newfound architectures for meta-heuristic music-inspired optimization algorithms. These proposed algorithms, with multi-stage computational, multi-dimensional, and multi-inhomogeneous structures, bring about a new direction in the architecture of meta-heuristic algorithms for solving complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data. The architectures of these new algorithms may also be appropriate for finding an optimal solution or a Pareto-optimal solution set with higher accuracy and speed in comparison to other optimization algorithms, when feasible regions of the solution space and/or dimensions of the optimization problem increase. This book, unlike conventional books on power systems problems that only consider simple and impractical models, deals with complicated, techno-economic, real-world, large-scale models of power systems operation and planning. Innovative applicable ideas in these models make this book a precious resource for specialists and researchers with a background in power systems operation and planning. Provides an understanding of the optimization problems and algorithms, particularly meta-heuristic optimization algorithms, found in fields such as engineering, economics, management, and operations research; Enhances existing architectures and develops innovative architectures for meta-heuristic music-inspired optimization algorithms in order to deal with complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data; Addresses innovative multi-level, techno-economic, real-world, large-scale, computational-logical frameworks for power systems operation and planning, and illustrates practical training on implementation of the frameworks using the meta-heuristic music-inspired optimization algorithms.
Author: Mohammad Fathi
Author: Mohammad Fathi
Author: Navid Razmjooy
Author: Mohamed Bakr
Author: Navid Razmjooy
Author: Kaushik Kumar
Author: Simone Göttlich
Author: A. Kaveh
Author: James A. Momoh
Author: Xu Andy Sun
Author: Mohammad Kiani-Moghaddam