IEEE Access (Jan 2024)
A Systematic Review of Optimization Approaches Employed in Digital Warehousing Transformation
Abstract
Digital transformation of warehousing is revolutionizing operations by integrating advanced technologies. Automated Guided Vehicles (AGVs) optimize the movement of goods, while Internet of Things (IoT) enhances connectivity and data collection for improved decision-making. Robots automate tasks like picking and packing, increasing efficiency and reducing errors. Blockchain technology enhances transparency and traceability in the supply chain, building trust and reducing fraud. Digital twins create virtual replicas of warehouses for simulation and optimization, enabling proactive problem-solving and improved resource allocation. Such transformation addresses the increasing complexity and dynamic nature of warehousing in the modern marketplace. This systematic literature review, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, investigates the role of optimization models in this digital shift from 2010 to 2023. The findings highlight the crucial enhancements and practical implications brought about by these technologies, showcasing their impact on streamlining operations. These improvements include advancements in path planning, task allocation, inventory management and storage assignment which significantly enhance operational effectiveness within warehousing. The results demonstrate a 25-30% increase in perishable food freshness, a 10% reduction in picking time, a 14.8% increase in space utilization, and a 9.95% decrease in total costs. Moreover, the findings call attention to the insufficient analysis on the economic implications of digital transformations in warehousing, notably in cost reductions and Return on Investment (ROI) evaluations which are crucial metrics for evaluating the financial success and wider benefits of digital transformation initiatives, such as customer satisfaction and revenue growth. The review also identifies critical research gaps, including the need to incorporate sustainability into optimization models, strategies for adapting to dynamic environments, the exploration of collaborative robots (cobots), and the optimization of reverse logistics and returns. This review provides a comprehensive foundation for future research and emphasizes the potential of digitalization to revolutionize warehousing practices through innovative optimization strategies and real-world applications.
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