Abstract
The conceptual phase of aircraft design is characterized by a significant degree of uncertainty in the initial data. This is largely due to the presence of random processes and incomplete information, requiring the use of non-deterministic parameters that cannot be defined by a precise number. These non-deterministic parameters are linked to parametric uncertainty, which is a key factor contributing to the increased risk of design errors. To address this challenge, this paper presents optimization models that formalize the tasks of parametric synthesis in aircraft conceptual design, with a focus on ensuring the reliability of design decisions. Probability theory and uncertainty theory are employed to represent non-deterministic parameters. The theory of uncertainty provides decision-makers with a powerful tool for constructing optimization models that encapsulate the formalized requirements of the designed system.