Dynamic allocation optimization of police warehouse based on integrated association rules and adaptive clustering

With the deepening of the reform of police equipment support system, the distribution of active service and militia equipment shows the characteristics of wide distribution and complex pedigree. To address these emerging challenges, it is imperative to adopt intelligent technologies and optimize operational efficiency in inventory management. Association rules can identify valuable equipment combinations and reveal correlation groups that enhance emergency scheduling decisions and equipment deployment strategies. However, existing methods only consider the optimization of association rules under the fixed storage strategy, ignore the adjustability of the storage layout, and lack the consideration of multiple storage layout in the storage process. To solve this problem, this paper proposes an optimization method combining association rules and dynamic clustering, which improves the traditional clustering method and combines the characteristics of the actual police warehouse. It can effectively reduce the average picking distance and congestion rate of robots and improve the warehouse utilization rate of the warehouse layout.