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Optimization in engineering = models and algorithms /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimization in engineering/ by Ramteen Sioshansi, Antonio J. Conejo.
Reminder of title:	models and algorithms /
Author:	Sioshansi, Ramteen.
other author:	Conejo, Antonio J.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xv, 412 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Mathematical optimization. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-56769-3
ISBN:	9783319567693

Optimization in engineering = models and algorithms /
Sioshansi, Ramteen.

Optimization in engineeringmodels and algorithms /[electronic resource] :by Ramteen Sioshansi, Antonio J. Conejo. - Cham :Springer International Publishing :2017. - xv, 412 p. :ill. (some col.), digital ;24 cm. - Springer optimization and its applications,v.1201931-6828 ;. - Springer optimization and its applications ;v. 16..

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.

ISBN: 9783319567693

Standard No.: 10.1007/978-3-319-56769-3doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Optimization in engineering = models and algorithms /
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300 $a xv, 412 p. : $b ill. (some col.), digital ; $c 24 cm.
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505 0 $a 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.
520 $a 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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