Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences

Abstract

The purpose of this paper is to introduce a new method for the design process of complex systems affected by epistemic uncertainty. In particular, a multi-layer network is proposed to model the whole design process and describe the transition between adjacent phases. Each layer represents a design phase where each node is a subsystem and each link a sharing of information. The network is used to quantify and propagate uncertainty through the different layers (design phases). At each phase, from phase A to phase F, the fidelity of the mathematical model describing each subsystem and component is increased. Thus, it can be considered as a multi-fidelity approach for the design of a complex system affected by epistemic uncertainty. The framework of Dempster-Shafer Theory of Evidence (DST) is used to model epistemic uncertainty. The model is then called Multi-Layer Evidence Network Model (ML-ENM).