Ultimate Pit Limit Optimization Using Keshtel Algorithm

Document Type : Research - Paper

Authors

1 M.Sc, Dept. of Mining Engineering, AmirKabir University of Technology, Tehran, Iran

2 Associate Professor, Dept. of Mining Engineering, AmirKabir University of Technology, Tehran, Iran

Abstract

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.

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References

  1. Espinoza, D., Goycoolea, M., Moreno, E., and Newman, A. (2013). “MineLib: a library of open pit mining problems”. Annals of Operations Research, 206(1): 93-114.
  2. اصانلو، م.؛ 1393؛ "روش های استخراج معدن سطحی(جلد اول)". انتشارات دانشگاه صنعتی امیر‌کبیر، تهران، ویرایش اول.
  3. Pana, M. T. (1965). “The simulation Approach to Open Pit Design”. 5th APCOM Symposium, Johannesburg, 139-144.
  4. Dowd, P. A., and Onur, A. H. (1993). “Open-pit optimization—part 1: optimal open-pit design”. Transactions of the Institutions of Mining and Metallurgy (Section A: Mining Technology), 102: 95-104.
  5. Lerchs, H., and Grossman, F. (1965). “Optimum Design of Open-Pit Mines”. Transaction CIM, 58: 47-54.
  6. Onur, A. H., and Dowd, P. (1993). “Open-pit optimization- Part 2: Production scheduling and inclusion of roadways”. Transactions of the Institutions of Mining and Metallurgy (Section A: Mining Technology), 102: 105-113.
  7. Picard, J. (1976). “Maximal closure of a graph and applications to combinatorial problems”. Management Science, 22: 1268-1272.
  8. Fraser, A. S. (1957a). “Simulation of genetic systems by automatic digital computers I. Introduction”. Australian Journal of Biological Sciences, 10(4): 484-491.
  9. Sattarvand, Javad. (2009). “Long-term open-pit planning by ant colony optimization”. Doctoral Dissertation, University Heidelberg, pp. 125.
  10. Karaboga, D. (2005). “An idea based on honey bee swarm for numerical optimization”. Technical Report-Tr06, October, Erciyes University, Türkiye.
  11. Raphael, B., and Smith, I. F. C. (2003a). “A direct stochastic algorithm for global search”. Journal of Applied Mathematics and Computation, 146(2-3): 729-758.
  12. Kim, Y. C. (1978). “Ultimate pit limit design methodologies using computer models-The state of the art”. Mining Engineering, 30(10): 1454-1459.
  13. اصانلو، م.؛ 1389؛ "عیار حد و نقش آن در طراحی معدن". انتشارات دانشگاه صنعتی امیرکبیر.
  14. Atashpaz-Gargari, E., and Lucas, C. (2007). “Imperialist Competitive Algorithm: An algorithm for optimization inspired by imperialistic competition”. IEEE Congress on Evolutionary Computation, 4661-4667.
  15. Hajiaghaei-Keshteli, M., and Aminnayeri, M. (2013). “Keshtel Algorithm (KA); a new optimization algorithm inspired by Keshtels’ feeding”. In: Proceeding in IEEE Conference on Industrial Engineering and Management Systems, Novel Metaheuristic, 2249-2253.
  16. Gupta, A., Singh, D., and Kaur, M. (2019). “An efficient image encryption using non dominated sorting genetic algorithm III based 4 D chaotic maps”. Journal of Ambient Intelligence and Humanized Computing, 11: 1309-1324. DOI: https://doi.org/10.1007/s12652-019-01493-x.
  17. Kennedy, J., and Eberhart, R. (1995). “Particle swarm optimization”. Proceedings of the IEEE International Conference on Neural Networks, Piscataway, New York, USA, 4: 1942-1948.
  18. حاج آقائی کشتلی، م.؛ 1394؛ "زمان بندی یکپارچه تولید و حمل ریلی در زنجیره تامین". رساله دکتری، دانشگاه صنعتی امیرکبیر.
  19. Hustrulid, W., Kuchta, M., and Martin, R. (2013). “Open pit mine planning and design, two volume set & CD-ROM pack”. CRC Press.
  20. Dadi, V., and Sattarvand, J. (2016). “Effects of the volatility of input parameters on cut-off grade optimisation, a case study of Sungun copper mine”. International Journal of Mining and Mineral Engineering, 7(1): 64-77.
  21. نوروزی، ا.؛ عطایی­‌پور، م.؛ 1396؛ "امکان‌سنجی کاربرد الگوریتم کلونی زنبور مصنوعی در برنامه‌ریزی تولید معادن". پایان نامه کارشناسی ارشد، دانشگاه صنعتی امیرکبیر.
Journal of Mineral Resources Engineering
Volume 8, Issue 4 - Serial Number 30
December 2023
Pages 79-102

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History

  • Receive Date: 26 August 2023
  • Revise Date: 22 November 2023
  • Accept Date: 24 October 2023

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