Research on Low-Carbon Multi-Modal Transportation Path Optimization: Incorporating Fuzzy Demand into Decision-Making Processes

Le résumé fourni par la source

In the context of increasing emphasis on low-carbon transportation and the challenges posed by uncertain demand, this study applies TOPSIS fuzzy theory and NSGA-III algorithm to optimize multi-modal transportation paths. By integrating these methods, we develop a novel approach that simultaneously considers carbon emissions, costs, efficiency, and customer satisfaction under conditions of fuzzy demand. The proposed method is evaluated through a series of experiments, which demonstrate that it significantly enhances optimization performance, reducing average costs and average emissions by 33.62% and 31.79%, respectively, compared to existing methods. Furthermore, the approach provides robust solutions that are resilient to uncertainties in demand. This research contributes to the advancement of low-carbon multi-modal transportation and offers practical insights for decision-makers in the transportation sector.

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