Sublevel stope layout planning through a greedy heuristic approach based on dynamic programming

References

• Afshin Mansouri, S., & Aktas, E. (2016). Minimizing energy consumption and makespan in a two-machine flowshop scheduling problem. Journal of the Operational Research Society, 67(11), 1382–1394. doi:10.1057/jors.2016.4
   Web of Science ®Google Scholar
• Alford, C. (1995). Optimization in underground mine design. 25th International Application of Computers and Operations Research in the Mineral Industry Symposium Proceedings. Brisbane, Australia: AusIMM.
   Google Scholar
• Anjomshoa, H., Albrecht, A. R., Lee, D. H., & Pudney, P. J. (2013). Optimising passing bay locations and vehicle schedules in underground mines. Journal of the Operational Research Society, 64(2), 241–249. doi:10.1057/jors.2012.42
   Web of Science ®Google Scholar
• Ataee-Pour, M. (1997). A new heuristic algorithm to optimise stope boundaries. Proceeding of the 2nd Regional APCOM Symposium on Computer Applications in the Mineral Industry. Moscow, Russia: Moscow State Mining University.
   Google Scholar
• Bai, X., Marcotte, D., & Simon, R. (2013). Underground stope optimization with network flow method. Computers & Geosciences, 52, 361–371. doi:10.1016/j.cageo.2012.10.019
   Web of Science ®Google Scholar
• 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(6), 427–434.
   Web of Science ®Google Scholar
• Cheimanoff, N., Deliac, E., & Mallet, J. (1989). GEOCAD: An alternative CAD and artificial intelligence tool that helps moving from geological resources to mineable reserves. In 21st International Symposium on the Application of Computers and Operations Research in the Mineral Industry. Colorado, USA: SME.
   Google Scholar
• Cressie, N. (1990). The origins of kriging. Mathematical Geology, 22(3), 239–252. doi:10.1007/BF00889887
   Google Scholar
• Foroughi, S., Hamidi, J. K., Monjezi, M., & Nehring, M. (2019). The integrated optimization of underground stope layout designing and production scheduling incorporating a non-dominated sorting genetic algorithm (NSGA-II). Resources Policy, 63, 101408. doi:10.1016/j.resourpol.2019.101408
   Web of Science ®Google Scholar
• Kovalyov, M. Y., Ng, C., & Cheng, T. E. (2007). Fixed interval scheduling: Models, applications, computational complexity and algorithms. European Journal of Operational Research, 178(2), 331–342. doi:10.1016/j.ejor.2006.01.049
   Web of Science ®Google Scholar
• Kumral, M. (2011). Incorporating geo-metallurgical information into mine production scheduling. Journal of the Operational Research Society, 62(1), 60–68. doi:10.1057/jors.2009.174
   Web of Science ®Google Scholar
• Kumral, M. (2012). Production planning of mines: Optimisation of block sequencing and destination. International Journal of Mining, Reclamation and Environment, 26(2), 93–103. doi:10.1080/17480930.2011.644474
   Web of Science ®Google Scholar
• Lovász, L. (1994). Stable sets and polynomials. Discrete Mathematics, 124(1-3), 137–153. doi:10.1016/0012-365X(92)00057-X
   Web of Science ®Google Scholar
• Menabde, M., Froyland, G., Stone, P., & Yeates, G. (2018). Mining schedule optimisation for conditionally simulated orebodies. In Advances in applied strategic mine planning (pp. 91–100. Cham, Switzerland: Springer.
   Google Scholar
• Nelis, G., Gamache, M., Marcotte, D., & Bai, X. (2016). Stope optimization with vertical convexity constraints. Optimization and Engineering, 17(4), 813–832. doi:10.1007/s11081-016-9321-6
   Web of Science ®Google Scholar
• Nezhadshahmohammad, F., Aghababaei, H., & Pourrahimian, Y. (2018). Draw rate management system using mathematical programming in extraction sequence optimisation of block cave mining. International Journal of Mining and Mineral Engineering, 9(1), 32–53. doi:10.1504/IJMME.2018.091217
   Google Scholar
• Ng, C. T., Cheng, T. C. E., Bandalouski, A. M., Kovalyov, M. Y., & Lam, S. S. (2014). A graph-theoretic approach to interval scheduling on dedicated unrelated parallel machines. Journal of the Operational Research Society, 65(10), 1571–1579. doi:10.1057/jors.2013.109
   Web of Science ®Google Scholar
• Nhleko, A. S., Tholana, T., & Neingo, P. N. (2018). A review of underground stope boundary optimization algorithms. Resources Policy, 56, 59–69. doi:10.1016/j.resourpol.2017.12.004
   Web of Science ®Google Scholar
• Nikbin, V., Ataeepour, M., Shahriar, K., Pourrahimian, Y., & MirHassani, S. A. (2019). Stope boundary optimization: A mathematical model and efficient heuristics. Resources Policy, 62, 515–526. doi:10.1016/j.resourpol.2018.10.007
   Web of Science ®Google Scholar
• Ovanic, J., & Young, D. (1995). Economic optimisation of stope geometry using separable programming with special branch and bound techniques. In Third Canadian conference on computer applications in the mineral industry. Rotterdam, Netherlands: Balkema.
   Google Scholar
• Pourrahimian, Y. (2013). Mathematical programming for sequence optimization in block cave mining (Doctoral Dissertation). Edmonton, AB: University of Alberta.
   Google Scholar
• Remy, N., Boucher, A., & Wu, J. (2009). Applied geostatistics with SGeMS: A user's guide. Cambridge: Cambridge University Press.
   Google Scholar
• Sakai, S., Togasaki, M., & Yamazaki, K. (2003). A note on greedy algorithms for the maximum weighted independent set problem. Discrete Applied Mathematics, 126(2–3), 313–322. doi:10.1016/S0166-218X(02)00205-6
   Web of Science ®Google Scholar
• Sandanayake, D. S. S., Topal, E., & Asad, M. W. A. (2015). A heuristic approach to optimal design of an underground mine stope layout. Applied Soft Computing, 30, 595–603. doi:10.1016/j.asoc.2015.01.060
   Web of Science ®Google Scholar
• Sari, Y. A. (2019). Novel Optimization Models for Surface and Underground Mine Planning (Doctoral Dissertation). Montreal, QC: McGill University.
   Google Scholar
• Topal, E., & Sens, J. (2010). A new algorithm for stope boundary optimization. Journal of Coal Science and Engineering (China), 16(2), 113–119. doi:10.1007/s12404-010-0201-y
   Google Scholar
• Villalba Matamoros, M. E., & Kumral, M. (2017). Heuristic stope layout optimisation accounting for variable stope dimensions and dilution management. International Journal of Mining and Mineral Engineering, 8(1), 1–18. doi:10.1504/IJMME.2017.10003210
   Google Scholar
• Villalba Matamoros, M. E., & Kumral, M. (2018). Underground mine planning: Stope layout optimisation under grade uncertainty using genetic algorithms. International Journal of Mining, Reclamation and Environment, 33(5), 353–370. doi:10.1080/17480930.2018.1486692
   Web of Science ®Google Scholar