Optimization concepts and applications in engineering

著者

書誌事項

Optimization concepts and applications in engineering

Ashok D. Belegundu, Tirupathi R. Chandrupatla

Cambridge University Press, 2019

3rd ed

  • : hardback

大学図書館所蔵 件 / 全3件

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注記

"First published by Prentice Hall 1999"--T.p. verso

"Second edition published by Cambridge University Press 2011"--T.p. verso

"First paperback edition 2014"--T.p. verso

"Third edition published 2019"--T.p. verso

Includes bibliographical references and index

内容説明・目次

内容説明

Organizations and businesses strive toward excellence, and solutions to problems are based mostly on judgment and experience. However, increased competition and consumer demands require that the solutions be optimum and not just feasible. Theory leads to algorithms. Algorithms need to be translated into computer codes. Engineering problems need to be modeled. Optimum solutions are obtained using theory and computers, and then interpreted. Revised and expanded in its third edition, this textbook integrates theory, modeling, development of numerical methods, and problem solving, thus preparing students to apply optimization to real-world problems. This text covers a broad variety of optimization problems using: unconstrained, constrained, gradient, and non-gradient techniques; duality concepts; multi-objective optimization; linear, integer, geometric, and dynamic programming with applications; and finite element-based optimization. It is ideal for advanced undergraduate or graduate courses in optimization design and for practicing engineers.

目次

  • Preface
  • 1. Preliminary concepts
  • 2. One-dimensional unconstrained minimization
  • 3. Unconstrained optimization
  • 4. Linear programming
  • 5. Constrained minimization
  • 6. Penalty functions, duality, and geometric programming
  • 7. Direct search methods for nonlinear optimization
  • 8. Multi-objective optimization
  • 9. Integer and discrete programming
  • 10. Dynamic programming
  • 11. Optimization applications for transportation, assignment, and network problems
  • 12. Finite element and simulation-based optimization
  • Index.

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