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Fundamentals of Optimization Techniques with Algorithms

Autor Sukanta Nayak
en Limba Engleză Paperback – 24 aug 2020
Optimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral role in computer-aided design. Fundamentals of Optimization Techniques with Algorithms presents a complete package of various traditional and advanced optimization techniques along with a variety of example problems, algorithms and MATLAB© code optimization techniques, for linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both theoretical and numerical perspectives in a clear and approachable way. In order to help the reader apply optimization techniques in practice, the book details program codes and computer-aided designs in relation to real-world problems. Ten chapters cover, an introduction to optimization; linear programming; single variable nonlinear optimization; multivariable unconstrained nonlinear optimization; multivariable constrained nonlinear optimization; geometric programming; dynamic programming; integer programming; multi-objective optimization; and nature-inspired optimization. This book provides accessible coverage of optimization techniques, and helps the reader to apply them in practice.


  • Presents optimization techniques clearly, including worked-out examples, from traditional to advanced
  • Maps out the relations between optimization and other mathematical topics and disciplines
  • Provides systematic coverage of algorithms to facilitate computer coding
  • Gives MATLAB© codes in relation to optimization techniques and their use in computer-aided design
  • Presents nature-inspired optimization techniques including genetic algorithms and artificial neural networks
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Specificații

ISBN-13: 9780128211267
ISBN-10: 0128211261
Pagini: 320
Ilustrații: 50 illustrations (25 in full color)
Dimensiuni: 152 x 229 x 24 mm
Greutate: 0.44 kg
Editura: ELSEVIER SCIENCE

Public țintă

Researchers and postgraduate students in mechanical engineering, electrical engineering, electronics, computer science, aerospace engineering, and related fields; Researchers and postgraduate students in mathematics; applied mathematics; and industrial mathematics.

Cuprins

1. Introduction to optimization2. Linear programming3. Single-variable nonlinear optimization4. Multivariable unconstrained nonlinear optimization5. Multivariable constrained nonlinear optimization6. Geometric programming7. Dynamic programming8. Integer programming9. Multiobjective optimization10. Nature-inspired optimization