This article examines the issues of assessing the sustainability of transport and logistics systems (TLS) under conditions of uncertainty, which play a key role in ensuring the effective functioning of supply chains. The sustainability of systems is analyzed in the context of their ability to adapt to external and internal influences, such as economic fluctuations, changes in demand, natural disasters and technological failures. In this paper, it is proposed to use fuzzy graph invariants, namely, a fuzzy dominating set, to assess and analyze the sustainability of transport and logistics systems under uncertainty. It is shown that a fuzzy dominating set allows solving the problem of placing distribution hubs in a transport and logistics system. Examples of finding fuzzy dominating sets for fuzzy and fuzzy temporal graphs as the models of transport and logistic system are presented. Fuzzy temporal graphs also allow for more adequate modeling and analysis of systems in cases where the time parameter is one of the important factors. The practical significance of the study lies in the possibility of designing a more reliable and adaptive TLS capable of functioning effectively under conditions of uncertainty. The results can be used to optimize logistics processes, reduce costs and increase the sustainability of supply chains. The findings also open prospects for further research in the field of integrating artificial intelligence methods and big data analysis in transport system management. Further research is proposed to be directed at integrating flow optimization methods considering time factors and developing digital twins of TLS.
