Given the amount of information processing required to study complexity, the use of computers and mathematical tools has been central to complex systems research. Probabilistic preference theory, including probabilistic-based expressions, refers to a conceptual framework using probabilities to align humans’ thoughts and perceptions.

During the past several years, the probabilistic preference theory has emerged as a hot research topic due to the fact that probabilistic preference representation models are natural ways to identify and model human-centric decision-making problems. It can be regarded as a bridge to connect the probabilistic uncertainty and fuzzy uncertainty and is a new branch of fuzzy systems. It has achieved a lot of good applications in either engineering or management science fields. Some papers have been published in recent years that clearly demonstrate this theory’s great potential for broad applications in the future. Studies in probabilistic preference theory and applications are promising and should be further researched to develop new theories and techniques, especially for new application areas in management sciences and engineering.

The aim of this Special Issue is to explore the up-to-date mathematical foundations, modelling, and synthesis algorithms concerning probabilistic preference theory. We hope to especially welcome studies about applications relevant to complex systems and practical engineering cases. We invite researchers and experts worldwide to submit original research articles and review articles on theoretical and experimental works related to probabilistic preference theory, including fuzzy modelling, clustering, optimization, and hybrid fuzzy systems. New interdisciplinary approaches and system-related research in probabilistic preference theory and applications in management, or strong conceptual foundations in newly evolving topics are acceptable.

Potential topics include but are not limited to the following:

• Probabilistic preference model and extensions
• Probabilistic linguistic term set and decision making
• Fuzzy optimization with probabilistic preference sets
• Fuzzy clustering with probabilistic preference sets
• Fuzzy reasoning with probabilistic preference sets
• Mathematical operations of probabilistic preferences
• Applications in healthcare management of probabilistic preference theory
• Applications in emergency, engineering, and risk management of probabilistic preference theory