In engineering problems, complex systems usually consist of many subsystems. The coupled disciplines represented by these subsystems are interrelated. Additionally, multi-source mixed uncertainties are accompanied by the transmission and accumulation of coupled information in complex systems. Therefore, how to model the system of the research object and its constituent disciplines is important. We need to use mathematical methods effectively to express the design optimization problem accurately. Moreover, we need to adopt appropriate uncertainty mathematical methods to quantify the uncertainty involved in design optimization. These are the main challenges in modelling and design optimization of complex systems considering mixed uncertainties.

To tackle the above challenges, the development of advanced modelling technology and design optimization algorithms of complex engineering systems considering mixed uncertainties are necessary. Meanwhile, the continuing development of engineering systems makes the existing modelling methods difficult to deal with all new problems efficiently. On the other hand, because of the limited time and cost, designers must select an appropriate method among various design and optimization methods to solve their problems. Consequently, more novel uncertainty-based design and optimization methods (UBDO) should be developed to provide more options for engineering designers. Generally, uncertainty system modelling is the preparatory stage of UBDO, including sensitivity analysis, system modelling, and uncertainty modelling. Alternatively, the uncertainty optimization process is the specific implementation stage. It mainly includes surrogate modelling, uncertainty analysis, and uncertainty optimization.

The aim of this Special Issue is to establish an academic exchange platform between experts and scholars. We also hope that this Special Issue establishes a common understanding about what is currently happening in the field and where the research is heading. This Special Issue will highlight the issues, discuss the possible solutions, and provide the data, models, and tools necessary to perform modelling technology and design optimization algorithms of complex systems considering mixed uncertainties. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Complex system modelling
• Multidisciplinary design optimization
• System reliability and risk assessment
• Optimization problem and computational methods
• Probabilistic and non-probabilistic uncertainty analysis
• Probabilistic physics of failure
• Uncertainty quantification and propagation
• Uncertainty-based design optimization
• Performance degradation modelling and analysis
• Sensitivity analysis
• Surrogate modelling
• Verification and validation