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Optimization methods and algorithms

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimization methods and algorithms/ by Anand J. Kulkarni.
Author:	Kulkarni, Anand Jayant.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xiii, 118 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1 Introduction to Optimization -- Chapter 2 Single Variable Optimization Methods -- Chapter 3 Multi Variable Optimization Methods -- Chapter 4 Graphical Optimization -- Chapter 5 Linear Programming Methods -- Chapter 6 Nature inspired Optimization Methods.
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization. -
Online resource:	https://doi.org/10.1007/978-981-96-9194-4
ISBN:	9789819691944

Optimization methods and algorithms
Kulkarni, Anand Jayant.

Optimization methods and algorithms[electronic resource] /by Anand J. Kulkarni. - Singapore :Springer Nature Singapore :2025. - xiii, 118 p. :ill. (some col.), digital ;24 cm.

Chapter 1 Introduction to Optimization -- Chapter 2 Single Variable Optimization Methods -- Chapter 3 Multi Variable Optimization Methods -- Chapter 4 Graphical Optimization -- Chapter 5 Linear Programming Methods -- Chapter 6 Nature inspired Optimization Methods.

The book thoroughly explains fundamental optimization concepts and terminology, including variables, parameters, constraints, bounds, and convexity. It also demonstrates how to formulate optimization problems using illustrative examples. Covering both single-variable and multi-variable optimization methods, the book provides theoretical insights, practical examples, and exercises, along with a graphical approach to problem-solving. In light of growing concerns about resource limitations and environmental impacts, this textbook addresses the need for efficient resource use amidst technological advancements and market competition. Students will appreciate the comprehensive coverage, supported by illustrations and exercises that deepen their understanding. Instructors will find it invaluable for classroom teaching, with accessible concepts and practical examples that highlight the nuances of optimization.

ISBN: 9789819691944

Standard No.: 10.1007/978-981-96-9194-4doiSubjects--Topical Terms:

517763
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Optimization methods and algorithms
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245 1 0 $a Optimization methods and algorithms $h [electronic resource] / $c by Anand J. Kulkarni.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a xiii, 118 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Chapter 1 Introduction to Optimization -- Chapter 2 Single Variable Optimization Methods -- Chapter 3 Multi Variable Optimization Methods -- Chapter 4 Graphical Optimization -- Chapter 5 Linear Programming Methods -- Chapter 6 Nature inspired Optimization Methods.
520 $a The book thoroughly explains fundamental optimization concepts and terminology, including variables, parameters, constraints, bounds, and convexity. It also demonstrates how to formulate optimization problems using illustrative examples. Covering both single-variable and multi-variable optimization methods, the book provides theoretical insights, practical examples, and exercises, along with a graphical approach to problem-solving. In light of growing concerns about resource limitations and environmental impacts, this textbook addresses the need for efficient resource use amidst technological advancements and market competition. Students will appreciate the comprehensive coverage, supported by illustrations and exercises that deepen their understanding. Instructors will find it invaluable for classroom teaching, with accessible concepts and practical examples that highlight the nuances of optimization.
650 0 $a Mathematical optimization. $3 517763
650 1 4 $a Mathematical and Computational Engineering Applications. $3 3592737
650 2 4 $a Optimization. $3 891104
650 2 4 $a Computational Intelligence. $3 1001631
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