Artificial Intelligence-Supported Hyperfuzzy VIKOR-DEA Framework for Sustainable Supply Chain and Energy Optimization in Smart Cities

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.

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Publication Details

Journal
Journal of Sustainable Development of Energy Water and Environment Systems
Published
2025-11-24
DOI
https://doi.org/10.13044/j.sdewes.d13.0620
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence-Supported Hyperfuzzy VIKOR-DEA Framework for Sustainable Supply Chain and Energy Optimization in Smart Cities

Fadoua Tamtam, Larbi Yacoubi, Amina Tourabi, Wissam Jenkal
Journal of Sustainable Development of Energy Water and Environment Systems
Electric Vehicles and Infrastructure
article

Artificial Intelligence-Supported Hyperfuzzy VIKOR-DEA Framework for Sustainable Supply Chain and Energy Optimization in Smart Cities

Fadoua Tamtam, Larbi Yacoubi, Amina Tourabi, Wissam Jenkal
article en

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.

Journal of Sustainable Development of Energy Water and Environment SystemsVol. 13(4)
Openalex Percentile: Top 64%
Electric Vehicles and Infrastructure
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Artificial Intelligence-Supported Hyperfuzzy VIKOR-DEA Framework for Sustainable Supply Chain and Energy Optimization in Smart Cities — Fadoua Tamtam, Larbi Yacoubi, et al. · Journal of Sustainable Development of Energy Water and Environment Systems (2025) | TGRS Research Map | TGRS