Application of Cognitive Logistic Networks for Route Optimization in Oman’s Logistics Operations

Résumé fourni par la source

Oman's transportation and logistics industry plays a crucial role in supporting the country's growth and diversification under Vision 2040. However, it encounters challenges regarding inefficient routes, scattered data, and limited real-time monitoring. To strengthen overall efficiency in operation and optimization of routes, this paper proposes a Cognitive Logistics Network (CLN) as a potential strategy. Logistics frameworks that are designed to learn, evolve, and execute decisions on their own are created practically through a Cognitive Logistics Network, which incorporates artificial intelligence, data analytics, and integrated systems. Intending to identify the most efficient transportation routes, this paper examines how cognitive networking will respond to parameters such as traffic scenarios, delivery preferences, and environmental constraints. The findings illustrate how deploying CLNs enhances Oman's transportation network's sustainability, integration, and transparency. Besides advancing the nation's transition towards Industry 4.0 and sustainable transportation developments across the GCC, this study improves smart transport logistics throughout Oman. The research project focuses on how implementing a cognitive framework can boost collaboration, reduce delivery times, and improve resource utilization throughout transportation networks to completely transform the logistics sector. The research paper analyzes ways of adopting the Cognitive Logistic Network (CLN) can improve decision-making, sustainability, and competitive advantage in the field of logistics. The objective of this research is to ensure that Oman and the wider GCC regions adopt smart and sustainable logistics strategies.

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