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 weig...

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Vydané v:2025 5th International Symposium on Computer Technology and Information Science (ISCTIS) s. 1296 - 1301
Hlavný autor: Zhang, Zhengrui
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Jazyk:English
Vydavateľské údaje: IEEE 16.05.2025
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Abstract 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.
AbstractList 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.
Author Zhang, Zhengrui
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  organization: Xinjiang University,School of Electrical Engineering,Urumqi,China
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Snippet This paper proposes a dynamic multi-factor optimization algorithm for elevator group control to address the challenges of unbalanced capacity utilization and...
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StartPage 1296
SubjectTerms Computational modeling
Dynamic scheduling
Dynamic scheduling algorithm
Elevator group control
Elevators
Heuristic algorithms
Load capacity balancing
Optimization
PLC-based control system
Processor scheduling
Programming
Real-time systems
Response cost optimization
Time factors
Transportation
Title Dynamic Multi-Factor Optimization for Elevator Group Control Scheduling
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