Fundamentals of Optimization Techniques with Algorithms

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 advancedMaps out the relations between optimization and other mathematical topics and disciplinesProvides systematic coverage of algorithms to facilitate computer codingGives MATLAB© codes in relation to optimization techniques and their use in computer-aided designPresents nature-inspired optimization techniques including genetic algorithms and artificial neural networks

1. Introduction to optimization
2. Linear programming
3. Single-variable nonlinear optimization
4. Multivariable unconstrained nonlinear optimization
5. Multivariable constrained nonlinear optimization
6. Geometric programming
7. Dynamic programming
8. Integer programming
9. Multiobjective optimization
10. Nature-inspired optimization