Specialists in optimization looking for a comprehensive and authoritative resource on robust optimization will be pleased to add Bertsimas and den Hertog’s work to their collection. Robust optimization addresses the critical issue of ensuring the validity of optimization approaches, even when the specific predicted input values used in the task are subject to uncertainty.

What I appreciate about this book is that the authors start from the basics, assuming no prior knowledge of robust optimization, though they do expect a solid understanding of linear and integer optimization. Reading this book without a strong intuition for optimization techniques would be challenging. Nevertheless, it begins with fundamental examples and comparisons, as well as the application of robust optimization in linear programming, making it accessible. As the discourse becomes more complex, the authors introduce each chapter’s importance with compelling real-life optimization examples. While I will not delve into all the details of the book’s contents, I want to emphasize that it thoroughly covers all the essential subfields of the area. A notable distinguishing feature compared to other comprehensive texts is its extensive exploration of adaptive robust optimization, which considers that conditions may change even during the optimization process itself.

An important advantage of this work is that it is authored by leading figures who have significantly contributed to the development of robust optimization. Consequently, the scientific context is thoroughly addressed, allowing readers to navigate the most important avenues in the field. However, this is not the first book on the subject. For instance, it can be compared to Robust optimization [1], a book by other pioneers in the field. While Robust and adaptive optimization is more comprehensive and up-to-date, its treatment of the material suggests that [1] might be a better starting point, particularly for courses in optimization within the engineering field. To serve as a conventional textbook, the book would benefit from more extensive examples and self-solution tasks. Nonetheless, for experts in optimization or mathematics, or PhD candidates interested in these fields, Bertsimas and den Hertog’s book stands as a valuable source of information, providing an insightful introduction to this important area of applied mathematics.

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