سامانه مدیریت نشریات علمی دانشگاه صنعتی شاهرود

Samanta, Gopinath, Dey, Tapan, Sinha, Suranjan. (1404). A Profit-based Mixed Integer Programming Model for Stope Boundary Optimization and Implementation in Indian Copper Deposits. , 16(4), 1179-1193. doi: 10.22044/jme.2025.14801.2812
Gopinath Samanta; Tapan Dey; Suranjan Sinha. "A Profit-based Mixed Integer Programming Model for Stope Boundary Optimization and Implementation in Indian Copper Deposits". , 16, 4, 1404, 1179-1193. doi: 10.22044/jme.2025.14801.2812
Samanta, Gopinath, Dey, Tapan, Sinha, Suranjan. (1404). 'A Profit-based Mixed Integer Programming Model for Stope Boundary Optimization and Implementation in Indian Copper Deposits', , 16(4), pp. 1179-1193. doi: 10.22044/jme.2025.14801.2812
Samanta, Gopinath, Dey, Tapan, Sinha, Suranjan. A Profit-based Mixed Integer Programming Model for Stope Boundary Optimization and Implementation in Indian Copper Deposits. , 1404; 16(4): 1179-1193. doi: 10.22044/jme.2025.14801.2812

A Profit-based Mixed Integer Programming Model for Stope Boundary Optimization and Implementation in Indian Copper Deposits

Journal of Mining and Environment
مقاله 3، دوره 16، شماره 4، مهر و آبان 2025، صفحه 1179-1193    اصل مقاله (3.66 M)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22044/jme.2025.14801.2812
نویسندگان
Gopinath Samanta* 1؛ Tapan Dey2؛ Suranjan Sinha3
1Senior Technologist (Mining), Process Technology Group, Tata Steel Limited, Jamshedpur, India,
2Data and analytics, TCS, Kolkata 700156, India
3Department of Mining Engineering, Indian Institute of Engineering, Science & Technology, Shibpur, Howrah
چکیده
The optimal layout of the stope (stope boundary) in an underground metal mine maximizes the profit of a deposit, subject to the geotechnical and operational mining constraints such as stope length, stope width, stope height. Various approaches have been introduced to address the stope boundary optimization problem, but due to the computational complexity and numerous practical constraints, the existing models offer partial solutions to the problem. In the present work, a mixed integer programming model has been developed by incorporating mining constraints in a three-dimensional framework.  This model is developed based on profit maximization. The sensitivity analysis applied in a case study mine indicates that the model is efficient in assessing the upside potential and downside risk of profit under fluctuating metal prices and mining costs. Additionally, it can be applied at different stages of mine design to facilitate resource appraisal, selection of stoping methods, and comprehensive mine planning. In a practical application on a real orebody, it shows that the proposed model can generate upto 37.32% more profit compared to current stope design practice in the mines.
کلیدواژه‌ها
Underground mining؛ Block model؛ Integer programming؛ Constraints؛ Sensitivity analysis
مراجع
  • Kumral, M. (2004). Genetic algorithms for optimization of a mining system under uncertainty. Production Planning & Control, 15 (1), 34–41.
  • Little, J., Topal, E., & Knights, P. (2011). Simultaneous optimization of stope layouts and long-term production schedules. Technol. Trans. Inst Min. Metall. Sect. A, 120, 129–136.
  • Ataee-Pour, M. (2000). A Heuristic Algorithm to Optimize Stope Boundaries. Doctor of Philosophy University of Wollongong, New South Wales.
  • Topal E., & Sens, J. (2010). A new algorithm for stope boundary optimization. J Coal Sci Eng, 16, 113–119.
  • Diogo, P. C., Andre, C. Z., & Italo, G. G. (2024). A Heuristic Methodology for Economic and Geomechanical Optimization in Sublevel Open Stoping Mining Method. Mining Metallurgy & Exploration, 41, 1645–1657.
  • Ovanic, J., & Young, D. S. (1995). Economic optimization of Stope geometry using separable programming with special branch and bound technique. In 3rd Canadian Conference on Computer Applications in the Minerals Industry, 129–135.
  • Ataee-Pour, M. (2004). Optimization of Stope limits using a heuristic approach. Mining Technology, 113, 123–128.
  • Shenavar, M., Ataee-pour, M., & Rahmanpour, M. (2020). A New Mathematical Model for Production Scheduling in Sub-level Caving Mining Method. Journal of Mining & Environment, 11(3), 765-778.
  • Riddle, M. (1977). A Dynamic Programming Solution of a Block Caving Mine Layout. Proceedings of the 14th International APCOM Symposium, New York.
  • Deraisme, J., Fouquent, C. D., & Fraisse, H. (1984). Geostatistical ore-body model for computer optimization of profits from different underground mining methods. 18th Int. APCOM, Melbourne, The Institution of Mining and Metallurgy, 583–590.
  • (1982). Image Analysis and Mathematical Morphology. Academic Press, New York.
  • Cheimanoff, N. M., Deliac, P., & Mallet, J. L. (1989). GEOCAD: an alternative CAD artificial intelligence tool that helps to move from geological resources to mineable reserves. 21st Int. APCOM, Colorado, SME, 471–478.
  • Alford C. (1995). Optimization in underground mine design. 25th Int. APCOM, Melbourne, Australasian Institute of Mining and Metallurgy, 213–218.
  • DATAMINE Studio RM v1.1 (2016). CAE Studio 3, Software Available at dataminesoftware.com.
  • Alford, C., Brazil, M., & Lee, D.H. (2007). Optimization in underground mining. Handbook of Operations Research in Natural Resources.
  • Gamze, E., & Mahmut, Y. (2017). Application of Three Existing Stope Boundary Optimisation Methods in an Operating Underground Mine. IOP Conf. Ser.: Earth Environ. Sci., 95, 042077.
  • Cawrse, (2001). Multiple pass floating Stope process. Strategic Mine Planning Conference, Perth, 87–94.
  • Ovanic, J., & Young, D.S. (1999). Economic Optimization of Open Stope Geometry. Proceedings of the 28th International APCOM Symposium, Colorado School of Mines, Golden.
  • Little, J., Knights, P., & Topal, E. (2013). Integrated optimization of underground mine design and scheduling. Journal of the South African Institute of Mining and Metallurgy, 113, 775-785.
  • Grieco, N., & Dimitrakopoulos, R. (2007). Managing grade risk in stope design optimization: probabilistic mathematical programming modal and application in sub-level stoping. Mining Technology, 116, 49–57.
  • Sandanayake, Topal, & Ali, A. (2015). A heuristic approach to optimal design of an underground mine stope layout. Applied Soft Computing, 30, 595–603.
  • Sens, J., &Topal, E. (2009). A new algorithm for stope boundary optimization. Aus IMM New Leaders Conference, Brisbane, 44–47.
  • Topal, E., & Sens, J. (2010). A new algorithm for stope boundary optimization, Coal Sci. Eng., 16 (2), 113–119.
  • Copland, T., & Nehring, M., (2016). Integrated optimization of stope boundary selection and scheduling for sublevel stoping operations, Journal of the Southern African Institute of Mining and Metallurgy, 116, 1135-1142.
  • Bai, X., Marcotte, D., & Simon, R. (2014). A heuristic sublevel stope optimizer with multiple raises. Journal of the Southern African Institute of Mining and Metallurgy, 114, 427-434.
  • Ataee-pour, M. (2005). A critical survey of the existing stope layout optimization techniques. Min. Sci. 41, 447–466.
  • Goldberg, J. B., & Winston, W.L. (2004). Operations Research: Applications and Algorithms. Thomson Brooks Cole, Belmont, CA.
آمار
تعداد مشاهده مقاله: 99
تعداد دریافت فایل اصل مقاله: 141