Optimization models for parametric synthesis of design solutions under uncertain parameters

Epistemic uncertainty may typically occur at preliminary stages of the technical objects design due to necessity to establish design solutions using the expertise data. To model the epistemic uncertainty occurring upon receipt of information on the parameters of the technical object under design from the experts, B.Liu’s uncertainty approach was chosen, as it offered analytical forms to calculate the functions number characteristics depending on parameters with epistemic uncertainty, that provides high computation efficiency when making optimization calculations. The article offers optimization models developed within the frameworks of uncertainty approach to solve the tasks of design solutions parametric synthesis in preliminary design of the technical objects. These models include optimization criteria ensuring safety and robustness of the design solutions. To apply the optimization models developed, the analytical forms of number characteristics of the target functions and limitations depending on uncertain inputs and parameters under optimization. Use of such analytical forms provides a solution of uncertainty of parameters under optimization due to the need to take into account the tolerances in production without statistic data and due to iteration nature of complex technical objects design processes, where the parameters under optimization may be adjusted.