- 1.0Impact Factor
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Stats, Volume 8, Issue 1
March 2025 - 24 articles
Cover Story: Cross-docking operations rely on precise scheduling and timely truck arrivals to ensure smooth logistics. Delays can disrupt operations, increasing storage costs and reducing efficiency. This paper explores the application of deep learning models—CNN, MLP, and RNN—to predict late truck arrivals and mitigate disruptions in cross-dock facilities. A comparative analysis evaluates their accuracy in forecasting delays. The findings highlight the potential of AI-driven predictive models in enhancing operational reliability, improving scheduling, and strengthening supply chain resilience. View this paper
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Stats - ISSN 2571-905X