Jaroslav Ramík Knihy

The book delves into the concepts of convexity and concavity in linear spaces, highlighting their significance in optimization problems, both single and multiple objectives. It explores generalized convex sets and concave functions, emphasizing their role in ensuring local optima can also serve as global optima, thus broadening their applicability. The latter sections focus on utilizing these concepts to tackle decision-making and optimization challenges under uncertainty, providing a comprehensive framework for addressing complex problems in various contexts.

Focusing on the intricacies of pairwise comparison matrices, this book delves into both deterministic and uncertain scenarios, including fuzzy and random elements. It explores the latest theories in decision-making processes and applies these concepts to prominent multicriteria decision-making methods such as AHP, PROMETHEE, and TOPSIS. Aimed at scholars in decision theory, operations research, and related fields, the text offers valuable insights into the mathematical foundations and practical applications of these matrices in various decision-making contexts.