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＜電子ブック＞
Optimization in Engineering : Models and Algorithms / by Ramteen Sioshansi, Antonio J. Conejo
(Springer Optimization and Its Applications. ISSN:19316836 ; 120)

版	1st ed. 2017.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2017
本文言語	英語
大きさ	XV, 412 p. 71 illus., 26 illus. in color : online resource
著者標目	*Sioshansi, Ramteen author Conejo, Antonio J author SpringerLink (Online service)
件　名	LCSH:Mathematical optimization LCSH:Industrial engineering LCSH:Production engineering FREE:Optimization FREE:Industrial and Production Engineering
一般注記	1. Optimization is Ubiquitous -- 2. Linear Optimization -- 3. Mixed-Integer Linear Optimization -- 4. Nonlinear Optimization -- 5. Iterative Solution Algorithms for Nonlinear Optimization -- 6. Dynamic Optimization -- A. Taylor Approximations and Definite Matrices -- B. Convexity -- Index This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields HTTP:URL=https://doi.org/10.1007/978-3-319-56769-3

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