Original scientific paper
https://doi.org/10.13044/j.sdewes.d13.0620
Artificial Intelligence-Supported Hyperfuzzy VIKOR-DEA Framework for Sustainable Supply Chain and Energy Optimization in Smart Cities
Fadoua Tamtam
; National School of Applied Sciences, IBN ZOHR University, Agadir, Morocco
Mustapha Amzil
; National School of Applied Sciences, IBN ZOHR University, Agadir, Morocco
Wissam Jenkal
; National School of Applied Sciences, IBN ZOHR University, Agadir, Morocco
Larbi Yacoubi
; National School of Applied Sciences, IBN ZOHR University, Agadir, Morocco
Amina Tourabi
; National School of Applied Sciences, IBN ZOHR University, Agadir, Morocco
Abstract
This study proposes an Artificial Intelligence-Supported Hyperfuzzy framework to evaluate hydrogen fuel cell technologies in Morocco's smart urban and supply chain ecosystems. Integrating compromise-ranking with efficiency benchmarking, the model addresses challenges in performance optimization, decision uncertainty, and supply integration. Key metrics—like power density, fuel efficiency, and system adaptability—are assessed through fuzzy logic and Artificial Intelligence-enhanced sensitivity analysis. Findings confirm that hydrogen-powered public transport offers superior efficiency and robustness, emerging as the top-ranked alternative. Artificial Intelligence strengthens traceability, weight calibration, and adaptability under expert preference variation. The study underscores the importance of supportive infrastructure, including refueling stations and grid-integrated systems, for scalable deployment. Results offer data-driven insights for policymakers and planners, guiding sustainable hydrogen strategies tailored to urban mobility and energy supply networks. By advancing decision accuracy under real-world uncertainty, this framework provides a replicable model for optimizing hydrogen-based solutions in smart cities.
Keywords
Artificial intelligence; Hyperfuzzy VIKOR-DEA; Hydrogen fuel cell technologies; Multi-criteria optimization; Supply chain optimization; Smart cities; Sensitivity analysis.
Hrčak ID:
342253
URI
Publication date:
18.5.2026.
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