Intended for advanced undergraduate/graduate students as well as scientists and engineers, this textbook presents a multi-disciplinary view of optimization, providing a thorough examination of algorithms, methods, techniques, and tools from diverse areas of optimization. Linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control, and stochastic optimal control are introduced in each self-contained chapter, with exercises, examples, and case studies, the true gems of this text. This third edition includes additional content in each chapter designed to clarify or enhance the exposition, and update methodologies and solutions. A new real-world case study related to sustainability is added in Chapters 2—7. GAMS, AIMMS, and MATLAB® files of case studies for Chapters 2, 3, 4, 5, and 7 are freely accessible electronically as extra source materials. A solutions manual is available to instructors who adopt the textbook for their course.
Algorithms for Optimization (2019) Название: Algorithms for Optimization Автор: Mykel J. Kochenderfer and Tim A. Wheeler Издательство: The MIT Press Год: 2019 Страниц: 521 Язык:...
Optimization in Electrical Engineering Название: Optimization in Electrical Engineering Автор: Mohammad Fathi and Hassan Bevrani Издательство: Springer Год: 2019 Формат: PDF, EPUB Размер:...
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Introduction to Applied Optimization, 3rd Edition 
