Optimization Techniques and Applications with Examples by Xin-She Yang offers a comprehensive guide to modern optimization applications and techniques, catering to newly emerging areas such as optimization, data science, machine intelligence, engineering, and computer sciences. The book introduces the fundamentals of various commonly used methods in optimization, encompassing both traditional and new algorithms. Covering a wide range of topics, including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming, it provides a broad perspective on the subject.

In addition to these core areas, the book delves into artificial neural networks, clustering and classifications, constraint-handling techniques, queueing theory, support vector machines, multi-objective optimization, evolutionary computation, and nature-inspired algorithms. Each topic is explained with step-by-step examples to illustrate how each method works, enabling readers to understand and apply these techniques effectively.

The author’s informal approach makes the book accessible for those seeking a rapid acquisition of basic knowledge in optimization, operational research, and applied data mining. Exercises throughout the text test the reader’s understanding and encourage practical application of the concepts covered. With its wide range of topics and detailed explanations, this resource is designed to be both an educational tool and a practical guide for professionals and students alike.

Published by Wiley on September 24, 2018, with ISBN-13: 978-1119490623, the book provides readers with valuable insights into modern optimization techniques and their applications in various fields. Ideal for anyone looking to deepen their understanding of optimization methods and their practical implications.

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