Fundamentals of Optimization Techniques with Algorithms

A complete package of traditional and advanced optimization techniques along with 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

Sukanta Nayak (Author)

9780128211267, Elsevier Science

Paperback, published 25 August 2020

320 pages, 50 illustrations (25 in full color)
22.9 x 15.1 x 2.1 cm, 0.52 kg

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.

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

Subject Areas: Maths for engineers [TBJ], Technology: general issues [TB]