Developing a Local Search Algorithm for Solving the Allocation and Dispatching Problem of Transportation Fleet in Open Pit Mines

Document Type : Research - Paper

Authors

1 Ph.D Student, Dept. of Mining Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

2 Professor, Dept. of Mining Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

3 Professor, Dept. of Civil and Environmental Engineering, Faculty of Engineering, University of Alberta, Edmonton, Canada

4 Assistant Professor, Dept. of Economic and Social Systems, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

5 Assistant Professor, Dept. of Mining Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

Loading and haulage operation in open pit mines is the last stage of the mining process. truck- shovel system, due to its many advantages  including high flexibility, is preferred for this operation. Due to high operating costs, proper fleet management and optimization can significantly affect the project economics. Truck allocation and dispatching issue is a very complex problem, especially in large mines with numerous loading and dumping points. Because of the problem size and complexity, employing mathematical methods is not justified due to very high solution time which leads to employing super computers. To overcome the aforesaid shortcoming, heuristic algorithms can be applied. In this paper, in MATLAB environment, a heuristic algorithm was developed to solve allocation and dispatching problem of transportation fleet of a real mine. According to the obtained results, a running time of 39 seconds was computed for the heuristic algorithm. Finally, the same problem was solved with an available mathematical model with a running time of 24 hours which shows the superiority of the proposed algorithm over the mathematical modeling.

Keywords

Main Subjects

References

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Journal of Mineral Resources Engineering
Volume 8, Issue 4 - Serial Number 30
December 2023
Pages 63-78

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History

  • Receive Date: 12 June 2022
  • Revise Date: 25 December 2022
  • Accept Date: 21 September 2022

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