Fuzzy Decision-Making and Risk Analysis in Transportation and Supply Chain Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 31
Special Issue Editor
Interests: fuzzy decision-making; transportation; industrial engineering; optimization; multiple attribute decision-making; expert systems; fuzzy logic; risk assessment; risk analysis in logistics system planning; dynamic optimization under uncertainty
Special Issue Information
Dear Colleagues,
In today’s rapidly evolving landscape, transportation and supply chain systems are increasingly exposed to environments defined by volatility, uncertainty, complexity, and ambiguity. These conditions have made decision-making a highly multifaceted process, where organizations must evaluate numerous qualitative and quantitative factors under conditions of imprecision, conflicting objectives, and risk. Traditional deterministic models like multiple-criteria decision-making methods often lack the flexibility to cope with these challenges, particularly when information is incomplete, ambiguous, or subject to rapid change.
This Special Issue seeks to highlight innovative research that integrates fuzzy logic, MCDM, and risk analysis to support more robust, adaptive, and informed decision-making in transportation and supply chain domains. The Fuzzy MCDM concept is especially well-suited for handling subjective judgments, linguistic assessments, and vague data, making it ideal for real-world problems where crisp values are not always available. Fuzzy MCDM methods offer structured tools for prioritizing and ranking alternatives across multiple, often conflicting, criteria. When these are combined with systematic risk analysis, decision-makers gain powerful frameworks for understanding uncertainties, quantifying potential impacts, and optimizing performance under risk-laden conditions.
We invite theoretical, methodological, and applied contributions that demonstrate how the Fuzzy MCDM methods including risk analysis can enhance operational effectiveness, improve resilience, and support strategic planning across all modes of transport and supply chain networks.
Dr. Nitidetch Koohathongsumrit
Guest Editor
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Keywords
- multiple criteria decision-making (MCDM)
- multiple attribute decision theory
- decision analysis
- single/hybrid MCDM methods
- fuzzy MCDM methods
- fuzzy set theory
- fuzzy logic
- transportation
- distribution planning
- optimization algorithm
- soft computing in logistics research
- supply chain/logistics management strategies and techniques
- multimodal transportation
- decision support system
- expert system
- supply chain performance management
- modelling and simulation of logistics and supply systems
- logistics and supply chain modelling
- green supply chain
- sustainability transportation systems
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