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Springer Optimization and Its Applications Ser.: Introduction to Applied Optimization by Urmila Diwekar (2020, Hardcover)

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About this product

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-103030554031

ISBN-139783030554033

eBay Product ID (ePID)14050400615

Product Key Features

Number of PagesXxix, 358 Pages

LanguageEnglish

Publication NameIntroduction to Applied Optimization

SubjectEngineering (General), Applied, Optimization

Publication Year2020

TypeTextbook

Subject AreaMathematics, Technology & Engineering

AuthorUrmila Diwekar

SeriesSpringer Optimization and Its Applications Ser.

FormatHardcover

Dimensions

Item Weight26.3 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Edition Number3

Series Volume Number22

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal519.6

Table Of Content1. Introduction.- 2. Linear Programming.- 3. Nonlinear Programming.-4. Discrete Optimization.- 5. Optimization Under Uncertainty.- 6. Multiobjective Optimization.- 7.Optimal Control and Dynamic Optimization.- Index.

SynopsisIntended for advanced undergraduate/graduate students as well as scientists and engineers, this textbook presents a multi-disciplinary view of optimization, providing a thorough examination of algorithms, methods, techniques, and tools from diverse areas of optimization. Linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control, and stochastic optimal control are introduced in each self-contained chapter, with exercises, examples, and case studies, the true gems of this text. This third edition includes additional content in each chapter designed to clarify or enhance the exposition, and update methodologies and solutions. A new real-world case study related to sustainability is added in Chapters 2--7. GAMS, AIMMS, and MATLAB® files of case studies for Chapters 2, 3, 4, 5, and 7 are freely accessible electronically as extra source materials. A solutions manual is available to instructors who adopt the textbook for their course. From the reviews: This work is definitely a welcome addition to the existing optimization literature, given its emphasis on modeling and solution practice, as well as its 'user-friendly' style of exposition. -- János D. Pintér, European Journal of Operations Research, Vol. 177, 2007 Urmila Diwekar's book on applied optimization is one of the few books on the subject that combines impressive breadth of coverage with delightful readability. In her exposition of concepts and algorithms in the major areas of optimization, she always goes to the heart of the matter and illustrates her explanations with simple diagrams and numerical examples. Graduate and undergraduate students, who constitute part of the target audience, should find this a very useful book. -- Jamshed A. Modi, Interfaces, Vol.36 (1), 2006 Optimization is a rich field with a strong history; this book nicely introduces both, moving from very introductory material to challenging techniques toward the end ... Examples range from quite simplistic through realistic difficult scheduling problems. Some examples resurface in different chapter with twists to demonstrate how different techniques are required for differing data and constraints. -- CHOICE, September 2004, Intended for advanced undergraduate/graduate students as well as scientists and engineers, this textbook presents a multi-disciplinary view of optimization, providing a thorough examination of algorithms, methods, techniques, and tools from diverse areas of optimization. Linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control, and stochastic optimal control are introduced in each self-contained chapter, with exercises, examples, and case studies, the true gems of this text. This third edition includes additional content in each chapter designed to clarify or enhance the exposition, and update methodologies and solutions. A new real-world case study related to sustainability is added in Chapters 2--7. GAMS, AIMMS, and MATLAB(R) files of case studies for Chapters 2, 3, 4, 5, and 7 are freely accessible electronically as extra source materials. A solutions manual is available to instructors who adopt the textbook for their course. From the reviews: This work is definitely a welcome addition to the existing optimization literature, given its emphasis on modeling and solution practice, as well as its 'user-friendly' style of exposition. -- János D. Pintér, European Journal of Operations Research, Vol. 177, 2007 Urmila Diwekar's book on applied optimization is one of the few books on the subject that combines impressive breadth of coverage with delightful readability. In her exposition of concepts and algorithms in the major areas of optimization, she always goes to the heart of the matter and illustrates her explanations with simple diagrams and numerical examples. Graduate and undergraduate students, who constitute part of the target audience, should find this a very useful book. -- Jamshed A. Modi, Interfaces , Vol.36 (1), 2006 Optimization is a rich field with a strong history; this book nicely introduces both, moving from very introductory material to challenging techniques toward the end ... Examples range from quite simplistic through realistic difficult scheduling problems. Some examples resurface in different chapter with twists to demonstrate how different techniques are required for differing data and constraints. -- CHOICE, September 2004, Optimization has pervaded all spheres of human endeavor. Although op- mization has been practiced in some form or other from the early prehistoric era, this area has seen progressive growth during the last ?ve decades. M- ern society lives not only in an environment of intense competition but is also constrained to plan its growth in a sustainable manner with due concern for conservation of resources. Thus, it has become imperative to plan, design, operate, and manage resources and assets in an optimal manner. Early - proaches have been to optimize individual activities in a standalone manner, however,thecurrenttrendistowardsanintegratedapproach:integratings- thesis and design, design and control, production planning, scheduling, and control. The functioning of a system may be governed by multiple perf- mance objectives. Optimization of such systems will call for special strategies for handling the multiple objectives to provide solutions closer to the systems requirement. Uncertainty and variability are two issues which render op- mal decision making di'cult. Optimization under uncertainty would become increasingly important if one is to get the best out of a system plagued by uncertain components. These issues have thrown up a large number of ch- lenging optimization problems which need to be resolved with a set of existing and newly evolving optimization tools. Optimization theory had evolved initially to provide generic solutions to optimizationproblemsinlinear,nonlinear,unconstrained,andconstrained- mains. Theseoptimization problems wereoften called mathematical progr- mingproblemswithtwodistinctiveclassi'cations,namelylinearandnonlinear programming problems., This book presents a view of optimization independent of any discipline. This new edition contains two new chapters, one on global optimization and one of a real-world case study that uses the principles from each chapter in the book.

LC Classification NumberQA402.5-402.6