European Journal of Computer Science and Information Technology (EJCSIT)

EA Journals

logistics optimization

Transforming Logistics Operations Through Cloud-Based Systems Integration (Published)

The integration of cloud-based systems is fundamentally transforming logistics operations by connecting previously isolated components across global supply networks. This integration directly impacts the physical movement of goods by synchronizing transportation networks, distribution center operations, and material handling processes. Organizations implementing cloud-based integration experience substantial improvements in fleet utilization, warehouse efficiency, and cross-docking operations. Transportation management systems optimize routing and carrier selection while warehouse and yard management systems enhance the physical handling of products. The architectural approaches powering these transformations enable real-time coordination of physical assets, from trucks and containers to forklifts and automated storage systems. Through real-world implementations, logistics providers demonstrate that cloud integration delivers measurable benefits in transportation network optimization, distribution center throughput, and inventory positioning, significantly reducing the physical distance products travel while improving service levels. This synchronized ecosystem enables logistics providers to effectively navigate increasingly complex global supply chains while optimizing the movement, storage, and handling of physical goods.

Keywords: Cloud integration, Supply chain visibility, logistics optimization, real-time data exchange, systems interoperability

The Transformative Impact of Artificial Intelligence on Supply Chain Management: A Contemporary Analysis (Published)

This article examines the transformative impact of Artificial Intelligence (AI) on supply chain management, focusing on four key areas: supply chain evolution, demand forecasting, warehouse automation, and logistics optimization. The article analyzes comprehensive data from global enterprises to demonstrate how AI implementation has revolutionized traditional supply chain processes. The article reveals significant improvements in operational efficiency, inventory management, and customer satisfaction through AI-driven solutions. The article highlights how machine learning algorithms and predictive analytics have enhanced demand forecasting accuracy, reduced supply chain disruptions, and optimized warehouse operations. Furthermore, the integration of AI-powered robotics and automation in logistics has led to substantial improvements in delivery performance, resource utilization, and environmental sustainability, marking a paradigm shift in supply chain management practices.

Keywords: Artificial Intelligence, demand forecasting, logistics optimization, supply chain management, warehouse automation

Real-Time Visibility: IoT Revolutionizes Inventory in Transit Tracking (Published)

The real-time visibility offered by Internet of Things tracking systems revolutionizes inventory management throughout worldwide supply chain operations. Such systems use connected sensors blended with wireless networks and cloud-based analytics that monitor shipping conditions along with location data and handling events between points A and B. The architecture has four operational segments that function together to acquire and transmit and process multi-dimensional streaming data. Implementing these solutions provides organizations with major operational advantages that include shorter transit times and decreased theft damage rates and higher inventory accuracies and better customer satisfaction rates. The implementation of IoT tracking systems meets challenges because of power usage problems, along with its connectivity requirements for remote locations as well as data safety concerns and compatibility issues with older systems. The adoption of emerging technologies focused on efficient hardware components and satellites and standardized framework standards compensates for these barriers to provide IoT tracking accessibility across multiple supply chain situations.

 

Keywords: environmental monitoring, inventory tracking, logistics optimization, real-time visibility, supply chain digitalization

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