Basics of Optimization Theory

Format: Hardback
Length: 147 pages
Publication date: 17 August 2023
Publisher: Springer International Publishing AG

This comprehensive book offers a thorough introduction to the fundamental tools of optimization methodology, encompassing linear programming, steepest descent, conjugate gradients, and the Karush-Kuhn-Tucker-John conditions. Each topic is developed within a specific physical model, ensuring that the strategy behind every step is driven by a logical, concrete, and easily visualized objective. A brief exploration of the Fibonacci search algorithm provides a captivating first encounter with optimization theory, while a review of the max-min exposition of one-dimensional calculus prepares readers for the more advanced topics later in the book.

Notable features of this text include innovative perspectives on the simplex algorithm and the Krushal-Kuhn-Tucker-John conditions, as well as a wealth of helpful diagrams. The author also provides pointers to references for readers who wish to delve deeper into rigorous definitions, proofs, elegant reformulations, and case studies. However, the book is sufficiently self-contained to serve as a reliable resource for readers who wish to leverage commercially available optimization software without investing the time to develop expertise in its intricacies.

In addition to its theoretical content, this book also emphasizes the practical applications of optimization techniques in various fields, such as engineering, economics, and operations research. It provides real-world examples and case studies to illustrate the effectiveness of optimization algorithms and their impact on decision-making processes. By presenting a balanced approach that combines theory and practice, this book aims to empower readers with the skills and knowledge necessary to solve complex optimization problems and achieve optimal solutions in their respective fields.

Dimension: 240 x 168 (mm)
ISBN-13: 9783031292187
Edition number: 1st ed. 2023