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Optimization in Engineering: Models and Algorithms: Springer Optimization and Its Applications, cartea 120

Autor Ramteen Sioshansi, Antonio J. Conejo
en Limba Engleză Paperback – 10 aug 2018
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.
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Specificații

ISBN-13: 9783319859965
ISBN-10: 331985996X
Pagini: 412
Ilustrații: XV, 412 p. 71 illus., 26 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.65 kg
Ediția:Softcover reprint of the original 1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Springer Optimization and Its Applications

Locul publicării:Cham, Switzerland

Cuprins

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.

Notă biografică

Ramteen Sioshansi is an associate professor in the Department of Integrated Systems Engineering at The Ohio State University. He holds a B.A., M.S., and Ph.D. from the University of California, Berkeley and an M.Sc. from the London School of Economics and Political Science. He has published over 50 peer-reviewed journals and has been the principal investigator of many research projects sponsored by public agencies and private industry. Antonio J. Conejo, professor at The Ohio State University, OH, US, received the B.S from Univ. P. Comillas, Spain, the M.S. from MIT, US and the Ph.D. from the Royal Institute of Technology, Sweden. He has published over 190 papers in SCI journals and is the author or coauthor of books published by Springer, John Wiley, McGraw-Hill and CRC. He has been the principal investigator of many research projects financed by public agencies and the power industry and has supervised 19 PhD theses. He is an IEEE Fellow.

Textul de pe ultima copertă

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.

Caracteristici

Offers a problem-solving approach and a large number of illustrative examples leading to a step-by-step formulation and solving of optimization problems Discussions are based on real-world examples and case studies Clarity of presentation maintains mathematical rigor Optimization textbook with broad appeal expressly for engineering upper-undergraduates/graduate students Includes supplementary material: sn.pub/extras