Fuzzy Multi-Criteria Decision Making for Sustainable Urban Mobility
Summary
Fuzzy Multi-Criteria Decision Making (MCDM) provides a powerful framework for evaluating and prioritising urban transport alternatives under conditions of uncertainty and imprecise information. By combining the mathematical rigour of fuzzy set theory with structured decision models, planners can incorporate expert judgements, stakeholder preferences and a range of environmental, social, economic and technical criteria into a single analysis. Typical steps include defining the decision context, selecting and weighting criteria through fuzzy membership functions, aggregating expert evaluations, ranking alternatives and conducting sensitivity checks. This approach has been applied to choices as diverse as bus fleet renewals, traffic management strategies, integration of autonomous and digital platforms, and micro-mobility schemes. In doing so, it has helped authorities to balance greenhouse-gas reduction, service accessibility, cost-effectiveness and public acceptance. Case studies from Asia, Europe and North America demonstrate how fuzzy MCDM aids robust, transparent and participatory decision processes, aligning transport investments with sustainable development goals and long-term resilience in growing urban environments.
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Fuzzy Multi-Criteria Decision Making for Sustainable Urban Mobility publication trend
The graph below shows the total number of articles in fuzzy multi-criteria decision making for sustainable urban mobility across all publications each year (not limited to Nature Index journals).
Technical terms
Fuzzy set theory: A mathematical framework that represents uncertainty by allowing elements to belong to a set with varying degrees of membership between 0 and 1.
Multi-Criteria Decision Making (MCDM): A structured process for evaluating and ranking alternatives against multiple, often conflicting, decision criteria.
Intuitionistic fuzzy set: An extension of fuzzy sets that assigns to each element a degree of membership, a degree of non-membership and a hesitation margin.
Closeness coefficient: A measure used in fuzzy decision models to quantify the proximity of each alternative to the ideal solution.
References
- An Integrated Intuitionistic Fuzzy Closeness Coefficient-Based OCRA Method for Sustainable Urban Transportation Options Selection. Axioms (2023).
- Accelerating the integration of the metaverse into urban transportation using fuzzy trigonometric based decision making. Engineering Applications of Artificial Intelligence (2024).
- Metaverse integration alternatives of connected autonomous vehicles with self-powered sensors using fuzzy decision making model. Information Sciences (2023).
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