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Optimization techniques in engineeringadvances and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Optimization techniques in engineeringedited by Anita Khosla ... [et al.]
其他題名:	advances and applications /
其他作者:	Khosla, Anita.
出版者:	Hoboken, NJ :John Wiley & Sons ;2023.
面頁冊數:	1 online resource (543 p.) :ill.
標題:	EngineeringMathematical models.
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119906391
ISBN:	9781119906391$q(electronic bk.)

Optimization techniques in engineeringadvances and applications /
Optimization techniques in engineeringadvances and applications /[electronic resource] :edited by Anita Khosla ... [et al.] - 1st ed. - Hoboken, NJ :John Wiley & Sons ;2023. - 1 online resource (543 p.) :ill. - Sustainable computing and optimization series. - Sustainable computing and optimization series..

Includes bibliographical references and index.

OPTIMIZATION TECHNIQUES IN ENGINEERING The book describes the basic components of an optimization problem along with the formulation of design problems as mathematical programming problems using an objective function that expresses the main aim of the model, and how it is to be either minimized or maximized; subsequently, the concept of optimization and its relevance towards an optimal solution in engineering applications, is explained. This book aims to present some of the recent developments in the area of optimization theory, methods, and applications in engineering. It focuses on the metaphor of the inspired system and how to configure and apply the various algorithms. The book comprises 30 chapters and is organized into two parts: Part I -- Soft Computing and Evolutionary-Based Optimization; and Part II -- Decision Science and Simulation-Based Optimization, which contains application-based chapters. Readers and users will find in the book: An overview and brief background of optimization methods which are used very popularly in almost all applications of science, engineering, technology, and mathematics; An in-depth treatment of contributions to optimal learning and optimizing engineering systems; Maps out the relations between optimization and other mathematical topics and disciplines; A problem-solving approach and a large number of illustrative examples, leading to a step-by-step formulation and solving of optimization problems. Audience Researchers, industry professionals, academicians, and doctoral scholars in major domains of engineering, production, thermal, electrical, industrial, materials, design, computer engineering, and natural sciences. The book is also suitable for researchers and postgraduate students in mathematics, applied mathematics, and industrial mathematics.

ISBN: 9781119906391$q(electronic bk.)Subjects--Topical Terms:

221320
Engineering
--Mathematical models.

LC Class. No.: TA342 / .O685 2023

Dewey Class. No.: 620.0015118

Optimization techniques in engineeringadvances and applications /
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520 $a OPTIMIZATION TECHNIQUES IN ENGINEERING The book describes the basic components of an optimization problem along with the formulation of design problems as mathematical programming problems using an objective function that expresses the main aim of the model, and how it is to be either minimized or maximized; subsequently, the concept of optimization and its relevance towards an optimal solution in engineering applications, is explained. This book aims to present some of the recent developments in the area of optimization theory, methods, and applications in engineering. It focuses on the metaphor of the inspired system and how to configure and apply the various algorithms. The book comprises 30 chapters and is organized into two parts: Part I -- Soft Computing and Evolutionary-Based Optimization; and Part II -- Decision Science and Simulation-Based Optimization, which contains application-based chapters. Readers and users will find in the book: An overview and brief background of optimization methods which are used very popularly in almost all applications of science, engineering, technology, and mathematics; An in-depth treatment of contributions to optimal learning and optimizing engineering systems; Maps out the relations between optimization and other mathematical topics and disciplines; A problem-solving approach and a large number of illustrative examples, leading to a step-by-step formulation and solving of optimization problems. Audience Researchers, industry professionals, academicians, and doctoral scholars in major domains of engineering, production, thermal, electrical, industrial, materials, design, computer engineering, and natural sciences. The book is also suitable for researchers and postgraduate students in mathematics, applied mathematics, and industrial mathematics.
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