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Combinatorial, linear, integer and n...

MacGregor Smith, J.

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Combinatorial, linear, integer and nonlinear optimization apps = COLINA Grande /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Combinatorial, linear, integer and nonlinear optimization apps/ by J. MacGregor Smith.
Reminder of title:	COLINA Grande /
Author:	MacGregor Smith, J.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xxi, 259 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction -- App Problem Formulation -- Combinatorial Optimization -- Linear Programming -- Integer Programming -- Nonlinear Programming -- AMPL NEOS Link -- Glossary.
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-030-75801-1
ISBN:	9783030758011

Combinatorial, linear, integer and nonlinear optimization apps = COLINA Grande /
MacGregor Smith, J.

Combinatorial, linear, integer and nonlinear optimization appsCOLINA Grande /[electronic resource] :by J. MacGregor Smith. - Cham :Springer International Publishing :2021. - xxi, 259 p. :ill. (some col.), digital ;24 cm. - Springer optimization and its applications,v. 1751931-6836 ;. - Springer optimization and its applications ;v. 175..

Introduction -- App Problem Formulation -- Combinatorial Optimization -- Linear Programming -- Integer Programming -- Nonlinear Programming -- AMPL NEOS Link -- Glossary.

This textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN) Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and related mathematics.

ISBN: 9783030758011

Standard No.: 10.1007/978-3-030-75801-1doiSubjects--Topical Terms:

723974
Mathematical optimization
--Data processing.

LC Class. No.: QA402.5 / .M33 2021

Dewey Class. No.: 519.6

Combinatorial, linear, integer and nonlinear optimization apps = COLINA Grande /
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245 1 0 $a Combinatorial, linear, integer and nonlinear optimization apps $h [electronic resource] : $b COLINA Grande / $c by J. MacGregor Smith.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xxi, 259 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer optimization and its applications, $x 1931-6836 ; $v v. 175
505 0 $a Introduction -- App Problem Formulation -- Combinatorial Optimization -- Linear Programming -- Integer Programming -- Nonlinear Programming -- AMPL NEOS Link -- Glossary.
520 $a This textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN) Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and related mathematics.
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