Dynamical aspects in fuzzy decision making

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The concept of fuzziness, inspired by Zadeh (1965), yields valuable insights in decision-making. Recently, the complexity of fuzzy decision-making has increased, with system dynamics being a significant factor. A dynamical approach was introduced by Bellman and Zadeh in their influential 1970 paper, which has since evolved into fuzzy mathematical programming, finding applications across various fields such as management science, operations research, control theory, engineering, systems analysis, computer science, and mathematical finance. Dynamic programming, highlighted in Bellman's 1957 work, is a key tool for addressing system dynamics. In their 1970 paper, Bellman and Zadeh proposed the optimality principle in fuzzy decision-making, leading to the development of fuzzy dynamic programming. This area has seen remarkable advancements since its inception. The volume presents ten reviewed papers exploring various dynamics, including not just temporal aspects but also structural elements of systems. It reviews fuzzy dynamic programming from its origins and examines its theoretical and practical development, aiming to enhance the understanding of dynamics in future studies.