Application of Keshtel algorithm for long term production planning in open pit mines

Articles in Press

Document Type : Research Article

Authors

1 Department of Mining Engineering, Amirkabir University of Technology, Tehran, Iran

2 Department of Mining Engineering / Amirkabir University of Technology

3 Mine exploitation, Mining engineering, Amirkabir university of technology, Tehran, Iran

Abstract

Ultimate pit limit optimization and production mine planning have always been the main challenges in the field of mining activities. The production mine planning can be determined through accurate methods and artificial intelligence techniques. While exact methods provide better and optimal results, they may require significant time to answer the problem due to the large number of blocks involved. In such cases, it is more suitable to use collective algorithms or a planned approach to determine the production mine planning. Production mine planning is similar to other optimization problems that can be addressed using logical algorithms in MATLAB software. In this study, Keshtel's algorithm, implemented in MATLAB, is utilized to optimize the production mine planning. Initially, Keshtel's algorithm is employed to solve the two-dimensional and three-dimensional problems. Subsequently, the Songun Copper Mine is chosen as a case study and the results of determining the production mine planning by Keshtel's algorithm are compared with the findings of NPV Scheduler software. The outcomes show that Keshtel's algorithm, used to determine the production mine planning of the Songun Copper Mine, differs by only 1.8%, when compared to the NPV Scheduler software. Moreover, the comparison of Keshtel's algorithm with the results of Gershon in two-dimensional production mine planning, as well as the comparison with NPV Scheduler software in three-dimensional problems, demonstrates its efficiency in solving these issues effectively.

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Amirkabir Journal of Civil Engineering

Articles in Press, Accepted Manuscript
Available Online from 07 January 2025

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