A method and system for dynamically calculating the minimum number of vehicles required for open-pit production
By collecting heterogeneous data from multiple sources to generate a comprehensive path difficulty coefficient, a mixed integer programming model was constructed and combined with a column generation algorithm and a distributed computing framework. This solved the problem of low scheduling efficiency of open-pit mine transportation vehicles, achieved dynamic optimization of equipment matching, improved scheduling efficiency and resource utilization, and reduced transportation costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CCTEG CHINA COAL RES INST
- Filing Date
- 2026-03-06
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies suffer from low scheduling efficiency and serious resource waste in open-pit mine transportation vehicles due to insufficient static modeling, multi-constraint coordination, and weak real-time response capabilities. They are unable to dynamically optimize equipment matching relationships, making it difficult to minimize transportation costs and maximize mining efficiency.
Collect heterogeneous data from multiple sources, generate a comprehensive path difficulty coefficient, construct a mixed integer programming model, solve the problem by combining a column generation algorithm with a distributed computing framework, and dynamically adjust the scheduling scheme through real-time data-driven incremental optimization and closed-loop feedback.
It significantly improves the real-time response capability of open-pit mine transportation scheduling to dynamic conditions such as ore grade fluctuations and equipment failures, reduces the number of vehicles required by 12% to 18%, improves vehicle utilization, reduces the time for adjusting scheduling schemes to the minute level, and reduces the solution time from the day level to the hour level, thereby minimizing transportation costs and maximizing mining efficiency.
Smart Images
Figure CN122414596A_ABST