Multi-level design optimization considering uncertainties in configurations and parameters

Abstract

In this research, a new approach is introduced for multi-level design optimization considering both parameter uncertainties and configuration uncertainties. In this work, an AND-OR tree is used to represent the generic design based on requirements. Nodes of the AND-OR tree are used to model partial design configuration solutions including the solutions considering possible configuration changes in the future. A node is further defined by parameters and their variations due to uncertainties. Design configuration candidates and their possible configuration changes are created from the AND-OR tree through a tree-based search. Each configuration candidate is defined by the parameters of the nodes and variations of these parameters. The optimal design configuration and its parameter values are achieved by a two-level optimization method. Parameter optimization is conducted for each design configuration candidate, while configuration optimization is conducted to obtain the best design configuration. Both the objective function and variation of the objective function due to uncertainties in configurations and parameters are considered in the multi-level optimization.