With the ready availability of inexpensive computer power, optimization has become one of the most important methodologies for solving difficult and often intractable problems in engineering, science, and business.
This comprehensive, detailed, and easy to read book treats unconstrained and constrained optimization in a unified manner from the user's perspective. The theory and practice of optimization are presented in terms of powerful gradient-based algorithms followed by real-life applications in the areas of pattern recognition, control systems, robotics, communication systems, and the design of digital filters.
Optimization: Algorithms and Applications provides sufficient background material on the applications considered to promote the understanding of the algorithms used, deals with the relevant parts of linear algebra in an appendix, and includes numerous solved examples and end-of-chapter problems that can be solved using MATLAB. The book is supported by detailed solutions of the end-of-chapter problems and an online collection of MATLAB m-files is provided for free access by readers over the Internet.