Research on Enterprise Warehouse Management and Automated Scheduling Based on Embedded Control System

Aiming at the problems of efficiency improvement and resource optimization in enterprise warehouse management, this paper designs and implements an automated scheduling system based on embedded control system. By analyzing the current status and shortcomings of the existing warehouse management system, the requirements of system design are clarified, and a modular architecture including perception layer, control layer and application layer is constructed. The system adopts a hybrid optimization algorithm, combining genetic algorithm and particle swarm optimization algorithm to optimize the scheduling decision process, and improves system performance through data compression and caching mechanism as well as real-time monitoring and fault prediction technology. Experimental results show that the automated scheduling system can maintain a low response time under different load conditions, and the optimized resource utilization rate is significantly improved in multiple key indicators. Research shows that the automated scheduling system based on embedded control system has significant advantages in improving warehouse management efficiency, optimizing resource allocation and reducing operating costs, and has broad application prospects.