The need for the application of uncertainty models has manifested in the fact that many complex engineering systems include conflict factors. Developing such models which can balance conflicting goals where there are many alternative courses of action available to the decision-makers when resources, time, and funds are limited is a large challenge. Computational methods (e.g., fuzzy set theory, neutrosophic theory, rough set theory, grey theory, Dempster-Shafer evidence theory, etc.) have everyday applications in decision-making about problems in complex engineering systems. In the last few years, applications of uncertainty models have been extended to solve real-world problems and other disciplines.

Complex engineering systems seek the application of scientific principles for practical objectives such as the processes, manufacture, design, and operation of products while accounting for constraints involving uncertainty factors. Various factors need to be considered to address complex engineering systems, so the application of computational methods has increased in the last time.

This Special Issue aims to collect original research articles that develop or apply uncertainty models (simulation, optimization, probability and statistics, decision theory, systems dynamics, multi-criteria decision making, etc.) in the field of engineering. Review articles that deal constructively with engineering complex systems debates are also welcome.

Potential topics include but are not limited to the following:

• Application of uncertainty models as a support in creating innovation in engineering
• Hybrid decision analysis for complex systems in engineering
• Innovative applications of uncertainty models
• Integration of novel uncertainty models
• Mathematical programming for complex systems in engineering
• Multi-criteria decision making (MCDM) under uncertainty in engineering
• Sustainable engineering decision-making with uncertainty
• Uncertainty models for risk analysis in engineering
• Application of computational methods in complex facility systems