keshtel algorithm

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 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.

To design an open pit mine, geological operations must be conducted, followed by the preparation of a three-dimensional model and mineral block model. The ultimate pit limit can be determined through accurate methods and artificial intelligence techniques. The problem of determining the ultimate pit limit is considered to be NP-hard, making it challenging to solve. 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 final range. Optimizing the determination of the ultimate pit limit is similar to other optimization problems that can be addressed using logical algorithms in MATLAB software. In this study, Keshtel algorithm, implemented in MATLAB, is utilized to optimize the final range. Initially, Keshtel algorithm is employed to solve the problem. Subsequently, the Songun copper mine is chosen as a case study for the two-dimensional and three-dimensional implementation, and the results of determining the ultimate pit limit are compared with both Keshtel algorithm and NPV Scheduler software. The findings reveal that Keshtel algorithm, used to determine the final limits of the Songun copper mine, differs by only 0.47% compared to the NPV Scheduler software. Moreover, the comparison of Keshtel algorithm with the results of Lerch Grossman in determining the two-dimensional final range, as well as the comparison with NPV Scheduler software in three-dimensional problems, demonstrates its efficiency in solving these issues effectively.