Dynamic Multi-Factor Optimization for Elevator Group Control Scheduling

This paper proposes a dynamic multi-factor optimization algorithm for elevator group control to address the challenges of unbalanced capacity utilization and conflict in response efficiency in multi-elevator systems. The algorithm integrates response time, energy consumption, and passenger-load weight into a dynamic scheduling cost model, which is implemented through Siemens S7-1200 PLC with integrated Ladder Diagram (LAD) and Structured Control Language (SCL) programming. The dynamic reallocation mechanism balances the workload through real-time cost analysis. Simulations on a threeelevator ten-floor model demonstrates that transportation efficiency has increased by 19.0% and the average waiting time has been reduced by 19.3%, validating the effectiveness of the framework in real-time scheduling.