Handbook of Optimisation Methods in Operations Research and Systems Analysis

Handbook of Optimisation Methods in Operations Research and Systems Analysis PDF Author: Luigi Cirocco
Publisher:
ISBN: 9781781543290
Category :
Languages : en
Pages :

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Optimization Methods in Operations Research and Systems Analysis

Optimization Methods in Operations Research and Systems Analysis PDF Author: K. V. Mital
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 352

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Optimization Methods in Operations Research and Systems

Optimization Methods in Operations Research and Systems PDF Author: Zhuhong Zhang
Publisher:
ISBN: 9781781547113
Category :
Languages : en
Pages : 300

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Optimization Methods in Operations Research and System Analysis

Optimization Methods in Operations Research and System Analysis PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 259

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Handbook of Optimization in Operations Research

Handbook of Optimization in Operations Research PDF Author: Peter Langlow
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 0

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Optimization Techniques in Operations Research

Optimization Techniques in Operations Research PDF Author: B. D. Sivazlian
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 502

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Deterministic Operations Research

Deterministic Operations Research PDF Author: David J. Rader
Publisher: John Wiley & Sons
ISBN: 1118627350
Category : Mathematics
Languages : en
Pages : 631

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Book Description
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations research: modeling real-world problems as linear optimization problem; designing the necessary algorithms to solve these problems; and using mathematical theory to justify algorithmic development. Treating real-world examples as mathematical problems, the author begins with an introduction to operations research and optimization modeling that includes applications form sports scheduling an the airline industry. Subsequent chapters discuss algorithm design for continuous linear optimization problems, covering topics such as convexity. Farkas’ Lemma, and the study of polyhedral before culminating in a discussion of the Simplex Method. The book also addresses linear programming duality theory and its use in algorithm design as well as the Dual Simplex Method. Dantzig-Wolfe decomposition, and a primal-dual interior point algorithm. The final chapters present network optimization and integer programming problems, highlighting various specialized topics including label-correcting algorithms for the shortest path problem, preprocessing and probing in integer programming, lifting of valid inequalities, and branch and cut algorithms. Concepts and approaches are introduced by outlining examples that demonstrate and motivate theoretical concepts. The accessible presentation of advanced ideas makes core aspects easy to understand and encourages readers to understand how to think about the problem, not just what to think. Relevant historical summaries can be found throughout the book, and each chapter is designed as the continuation of the “story” of how to both model and solve optimization problems by using the specific problems-linear and integer programs-as guides. The book’s various examples are accompanied by the appropriate models and calculations, and a related Web site features these models along with MapleTM and MATLAB® content for the discussed calculations. Thoroughly class-tested to ensure a straightforward, hands-on approach, Deterministic Operations Research is an excellent book for operations research of linear optimization courses at the upper-undergraduate and graduate levels. It also serves as an insightful reference for individuals working in the fields of mathematics, engineering, computer science, and operations research who use and design algorithms to solve problem in their everyday work.

Optimization Methods in Operations Research and Systems Analysis

Optimization Methods in Operations Research and Systems Analysis PDF Author: K V Mital
Publisher: New Age International
ISBN: 9788122408737
Category : Linear programming
Languages : en
Pages : 408

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Book Description
The Mathematical Aspects Of Operations Research And Systems Analysis Concerned With Optimization Of Objectives Form The Subject Of This Book. In Its Revised, Updated And Enlarged Third Edition, Discussion On Linear Programming Has Been Expanded And Recast With Greater Emphasis On Duality Theory, Sensitivity Analysis, Parametric Programming, Multiobjective And Goal Programming And Formulation And Solution Of Practical Problems. Chapters On Nonlinear Programming Include Integer Programming, Kuhn-Tucker Theory, Separable And Quadratic Programming, Dynamic Programming, Geometric Programming And Direct Search And Gradient Methods. A Chapter On Theory Of Games Is Also Included. A Short Note On Karmarkars Projective Algorithm Is Given In The Appendix.The Book Keeps In View The Needs Of The Student Taking A Regular Course In Operations Research Or Mathematical Programming, And Also Of Research Scholars In Other Disciplines Who Have A Limited Objective Of Learning The Practical Aspects Of Various Optimization Methods To Solve Their Special Problems. For The Former, Illustrative Solved Examples And Unsolved Examples At The End Of Each Chapter, Small Enough To Be Solved By Hand, Would Be Of Greater Interest, While For He Latter, Summaries Of Computational Algorithms For Various Methods Which Would Help Him To Write Computer Programmes To Solve Larger Problems Would Be More Helpful. A Few Computer Programmes In Fortran Iv Have Also Been Given In The Appendix.

Operations Research

Operations Research PDF Author: Michael Carter
Publisher: CRC Press
ISBN: 1498780113
Category : Business & Economics
Languages : en
Pages : 448

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Book Description
Operations Research: A Practical Introduction is just that: a hands-on approach to the field of operations research (OR) and a useful guide for using OR techniques in scientific decision making, design, analysis and management. The text accomplishes two goals. First, it provides readers with an introduction to standard mathematical models and algorithms. Second, it is a thorough examination of practical issues relevant to the development and use of computational methods for problem solving. Highlights: All chapters contain up-to-date topics and summaries A succinct presentation to fit a one-term course Each chapter has references, readings, and list of key terms Includes illustrative and current applications New exercises are added throughout the text Software tools have been updated with the newest and most popular software Many students of various disciplines such as mathematics, economics, industrial engineering and computer science often take one course in operations research. This book is written to provide a succinct and efficient introduction to the subject for these students, while offering a sound and fundamental preparation for more advanced courses in linear and nonlinear optimization, and many stochastic models and analyses. It provides relevant analytical tools for this varied audience and will also serve professionals, corporate managers, and technical consultants.

Handbook of Optimization in Operations Research

Handbook of Optimization in Operations Research PDF Author: Peter Langlow
Publisher:
ISBN: 9781781542934
Category : Mathematical optimization
Languages : en
Pages : 300

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Book Description
Intended as a text covering the central concepts of practical optimization techniques, this book is designed for either self-study by professionals or classroom work at the undergraduate or graduate level for students who have a technical background in engineering, mathematics, or science.