Smart Supply Chains: Leveraging AI and Digital Transformation for Route and Distance Optimization
Keywords:
Supply Chain Optimization, Artificial Intelligence (AI), Digital Transformation, Route Optimization, IoT (Internet of Things), RPA (Robotic Process Automation), Digital Twins, Predictive Analytics, Smart Supply Chains, Sustainability in Logistics.Abstract
The global supply chain landscape is undergoing a transformation driven by the integration of artificial intelligence (AI) and digital technologies. Traditional supply chains often face challenges such as inefficient route planning, rising fuel costs, and growing environmental concerns. This research explores how AI, IoT, RPA, and digital twins are enabling smart supply chains, focusing on route and distance optimization. Through a comprehensive review of industry practices and case studies, the paper highlights the cost, time, and environmental benefits of leveraging AI-driven solutions. Key findings reveal that real-time route optimization algorithms, IoT-enabled fleet management, and predictive analytics significantly reduce operational inefficiencies and enhance customer satisfaction (Raj et al., 2020; Kim et al., 2021). Furthermore, the study examines challenges in data integration, cost scalability, and regulatory compliance, offering actionable recommendations for successful implementation (Ivanov et al., 2020; Ghosh et al., 2021). By showcasing examples from leading companies such as Amazon, Walmart, and emerging players like QXO, the paper underscores the critical role of digital transformation in shaping sustainable and efficient supply chains (Van Meldert & De Boeck, 2016).
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Ghosh, S., Biswas, T., & Dutta, P. (2021). "Economic implications of AI adoption in logistics." Economic Modelling. https://doi.org/10.1016/j.econmod.2021.02.004
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Ghosh, S., Biswas, T., & Dutta, P. (2021). "Economic implications of AI adoption in logistics." Economic Modelling. https://doi.org/10.1016/j.econmod.2021.02.004.
Raj, A., & Sharma, M. (2020). "Machine learning in supply chain optimization." Computers in Industrial Engineering. https://doi.org/10.1016/j.cie.2020.107632
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