Multi-stage optimization framework for the real-time truck decision problem in open-pit mines: a case study on Sungun copper mine

References

• R. Mena, Z. Enrico, K. Fredy, and A. Adolfo, Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints, Int. J. Min. Sci. Technol. 23(1) (2013), pp. 113–119. doi:10.1016/j.ijmst.2013.01.017.
   Google Scholar
• S. Alarie and M. Gamache, Overview of solution strategies used in truck dispatching systems for open pit mines, Int. J. Surf. Min. Reclam. Environ. 16(1) (2002), pp. 59–76. doi:10.1076/ijsm.16.1.59.3408.
   Google Scholar
• M.J.F. Souza, I.M. Coelho, S. Ribas, H.G. Santos, and L.H.C. Merschmann, A hybrid heuristic algorithm for the open-pit-mining operational planning problem, Eur. J. Oper. Res. 207(2) (2010), pp. 1041–1051. doi:10.1016/j.ejor.2010.05.031.
   Web of Science ®Google Scholar
• E. Torkamani and H. Askari-Nasab, A linkage of truck-and-shovel operations to short-term mine plans using discrete-event simulation, Int. J. Min. Mineral Eng. 6(2) (2015), pp. 97–118. doi:10.1504/IJMME.2015.070367.
   Google Scholar
• A.S. Hashemi and J. Sattarvand, Simulation based investigation of different fleet management paradigms in open pit mines-A case study of Sungun copper mine//symulacje I Badania Różnych Paradygmatów Wykorzystania Floty Pojazdów I Urządzeń W Kopalniach Odkrywkowych, Studium Przypadku: Kopalnia Miedzi W Sungun, Arch. Min. Sci. 60(1) (2015), pp. 195–208.
   Google Scholar
• A. Moradi-Afrapoli, M. Tabesh, and H. Askari-Nasab, A multiple objective transportation problem approach to dynamic truck dispatching in surface mines, Eur. J. Oper. Res. 276(1) (2019), pp. 331–342. doi:10.1016/j.ejor.2019.01.008.
   Web of Science ®Google Scholar
• B. Ozdemir and M. Kumral, Simulation-based optimization of truck-shovel material handling systems in multi-pit surface mines, Simul. Model. Pract. Theory 95 (2019), pp. 36–48. doi:10.1016/j.simpat.2019.04.006.
   Web of Science ®Google Scholar
• M. Yeganejou, M. Badiozamani, A. Moradi-Afrapoli, and H. Askari-Nasab, Integration of simulation and dispatch modelling to predict fleet productivity: An open-pit mining case, Min. Technol. (2021), pp. 1–13.
   Google Scholar
• H. Bnouachir, H.A. Semmar, and H. Medromi, Intelligent fleet management system for open pit mine, Int. J. Adv. Comput. Sci. Appl. 11(5) (2020), pp. 327–332. doi:10.14569/IJACSA.2020.0110543.
   Google Scholar
• A. Moradi-Afrapoli and H. Askari-Nasab, Mining fleet management systems: A review of models and algorithms, Int. J. Min. Reclam. Environ. 33(1) (2017), pp. 1–19.
   Web of Science ®Google Scholar
• J.W. White and J.P. Olson, Computer-based dispatching in mines with concurrent operating objectives, Min. Eng. Littleton. 38(11) (1986), pp. 1045–1054.
   Google Scholar
• J.P. Olson, S.I. Vohnout, and J. White, On improving truck/shovel productivity in open pit mines, CIM Bull. 86(973) (1993), pp. 43–49.
   Google Scholar
• M. Munirathinam and J.C. Yingling, A review of computer-based truck dispatching strategies for surface mining operations, Int. J. Surf. Min. Reclam. Environ. 8(1) (1994), pp. 1–15. doi:10.1080/09208119408964750.
   Google Scholar
• F. Soumis, F. Ethier, and J. Elbrond Evaluation of the new truck dispatching in the Mount Wright Mine. In: 21st Application of Computers and Operations Research in the Minerals Industry, SME, (1990), p. 674–682.
   Google Scholar
• Z. Li, A methodology for the optimum control of shovel and truck operations in open-pit mining, Min. Sci. Technol. 10(3) (1990), pp. 337–340. doi:10.1016/0167-9031(90)90543-2.
   Google Scholar
• V.A. Temeng, F.O. Otuonye, and J.O. Frendewey, Real-time truck dispatching using a transportation algorithm, Int. J. Surf. Min., Reclam. Environ. 11(4) (1997), pp. 203–207. doi:10.1080/09208119708944093.
   Google Scholar
• R.F. Subtil, D.M. Silva, and J.C. Alves, A practical approach to truck dispatch for open pit mines, in 35th APCOM, University of Wollongong, Wollongong, NSW, Australia, 2011 , pp. 765–777.
   Google Scholar
• T. Markeset and U. Kumar Application of LCC techniques in selection of mining equipment and technology. Mine planning and equipment selection 2000. In Proceedings of the Ninth International Symposium on Mine Planningand Equipment Selection, Nov 6–9, Athens, Greece. A.A. Balkema, Rotterdam (2002), pp. 635–640.
   Google Scholar
• B. Samanta, B. Sarkar, and S. Mukherjee, Selection of opencast mining equipment by a multi-criteria decision-making process, Min. Technol. 111(2) (2002), pp. 136–142. doi:10.1179/mnt.2002.111.2.136.
   Google Scholar
• H. Jang and E. Topal, A review of soft computing technology applications in several mining problems, Appl. Soft Comput. 22 (2014), pp. 638–651. doi:10.1016/j.asoc.2014.05.019.
   Web of Science ®Google Scholar
• S.D. Smith, G.S. Wood, and M. Gould, A new earthworks estimating methodology, Constr. Manage. Econ. 18(2) (2000), pp. 219–228. doi:10.1080/014461900370843.
   Google Scholar
• C.N. Burt and L. Caccetta, Equipment selection for surface mining: A review, Interfaces (Providence). 44(2) (2014), pp. 143–162. doi:10.1287/inte.2013.0732.
   Web of Science ®Google Scholar
• C. Burt, L. Caccetta, P. Welgama, and L. Fouché, Equipment selection with heterogeneous fleets for multiple-period schedules, J. Oper. Res. Soc. 62(8) (2011), pp. 1498–1509. doi:10.1057/jors.2010.107.
   Web of Science ®Google Scholar
• M. Fisonga, V. Mutambo, and R.F. Colmenares, Optimization of the fleet per shovel productivity in surface mining: Case study of Chilanga Cement, Lusaka Zambia, Cogent Eng. 4(1) (2017), pp. 1–16. doi:10.1080/23311916.2017.1386852.
   Web of Science ®Google Scholar
• O. Pasch and S. Uludag, Optimization of the load-and-haul operation at an opencast colliery, J. South. Af. Inst. Min. Metall. 118(5) (2018), pp. 449–456. doi:10.17159/2411-9717/2018/v118n5a1.
   Web of Science ®Google Scholar
• M. Mohtasham, H. Mirzaei-Nasirabad, H. Askari-Nasab, and B. Alizadeh, Truck fleet size selection in open-pit mines based on the match factor using a MINLP model, Min. Technol. 130(3) (2021), pp. 1–17. doi:10.1080/25726668.2021.1919374.
   Google Scholar
• A. Michiotis, D. Xerocostas, and N. Galitis, A new integrated system for selecting mining equipment, Comput. Ind. Eng. 34(2) (1998), pp. 391–397. doi:10.1016/S0360-8352(97)00164-2.
   Web of Science ®Google Scholar
• D.J. Edwards, H. Malekzadeh, and S.B. Yisa, A linear programming decision tool for selecting the optimum excavator, Struct. Surv. 19(2) (2001), pp. 113–120. doi:10.1108/EUM0000000005628.
   Google Scholar
• Z. Fu, E. Topal, and O. Erten, Optimisation of a mixed truck fleet schedule through a mathematical model considering a new truck-purchase option, Min. Technol. 123(1) (2014), pp. 30–35. doi:10.1179/1743286314Y.0000000055.
   Google Scholar
• A.A. Bazzazi, M. Osanloo, and B. Karimi, Deriving preference order of open pit mines equipment through MADM methods: Application of modified VIKOR method, Expert Syst. Appl. 38(3) (2011), pp. 2550–2556. doi:10.1016/j.eswa.2010.08.043.
   Web of Science ®Google Scholar
• R. Ganguli and S. Bandopadhyay, Expert system for equipment selection, Int. J. Surf. Min., Reclam. Environ. 16(3) (2002), pp. 163–170. doi:10.1076/ijsm.16.3.163.7420.
   Google Scholar
• S.H.L. Mirhosseyni and P. Webb, A hybrid fuzzy knowledge-based expert system and genetic algorithm for efficient selection and assignment of material handling equipment, Expert Syst. Appl. 36(9) (2009), pp. 11875–11887. doi:10.1016/j.eswa.2009.04.014.
   Web of Science ®Google Scholar
• A. Lashgari, A. Yazdani–chamzini, M.M. Fouladgar, E.K. Zavadskas, S. Shafiee, and N. Abbate, Equipment selection using fuzzy multi criteria decision making model: Key study of Gole Gohar iron mine, Eng. Econ. 23(2) (2012), pp. 125–136. doi:10.5755/j01.ee.23.2.1544.
   Google Scholar
• N. Ataeepour and E. Baafi, ARENA simulation model for truck-shovel operation in despatching and non-despatching modes, Int. J. Surf. Min., Reclam. Environ. 13(3) (1999), pp. 125–129. doi:10.1080/09208119908944228.
   Google Scholar
• P. Chaowasakoo, H. Seppälä, H. Koivo, and Q. Zhou, Improving fleet management in mines: The benefit of heterogeneous match factor, Eur. J. Oper. Res. 261 (3) (2017), pp. 1052–1065. doi:10.1016/j.ejor.2017.02.039.
   Web of Science ®Google Scholar
• S. Dindarloo, M. Osanloo, and S. Frimpong, A stochastic simulation framework for truck and shovel selection and sizing in open pit mines, J. South. Afr. Inst. Min. Metall. 115(3) (2015), pp. 209–219. doi:10.17159/2411-9717/2015/v115n3a6.
   Web of Science ®Google Scholar
• S. Que, A. Anani, and K. Awuah-Offei, Effect of ignoring input correlation on truck–shovel simulation, Int. J. Min., Reclam. Environ. 30(5) (2016), pp. 405–421. doi:10.1080/17480930.2015.1099188.
   Web of Science ®Google Scholar
• W. Zeng, E. Baafi, and D. Walker, A simulation model to study bunching effect of a truck-shovel system, Int. J. Min., Reclam. Environ. 33(2) (2019), pp. 102–117. doi:10.1080/17480930.2017.1348284.
   Web of Science ®Google Scholar
• A. Jaoua, D. Riopel, and M. Gamache, A simulation framework for real-time fleet management in internal transport systems, Simul. Modell. Pract. Theory 21(1) (2012), pp. 78–90. doi:10.1016/j.simpat.2011.10.003.
   Web of Science ®Google Scholar
• M.S. Shishvan and J. Benndorf, Simulation-Based optimization approach for material dispatching in continuous mining systems, Eur. J. Oper. Res. 275(3) (2019), pp. 1108–1125. doi:10.1016/j.ejor.2018.12.015.
   Web of Science ®Google Scholar
• S.P. Upadhyay and H. Askari-Nasab, Simulation and optimization approach for uncertainty-based short-term planning in open pit mines, Int. J. Min. Sci. Technol. 28(2) (2018), pp. 153–166. doi:10.1016/j.ijmst.2017.12.003.
   Web of Science ®Google Scholar
• S. Dindarloo and E. Siami-Irdemoosa Merits of discrete event simulation in modeling mining operations. SME Annual Meeting 2016, Phoenix, AZ, 24–26.
   Google Scholar
• R.S. Suglo and S. Al-Hassan, Use of simulation techniques in determining the fleet requirements of an open pit mine, Ghana Min. J. 9 (2007), pp. 25–32.
   Google Scholar
• Y. Tan, K. Miwa, U. Chinbat, and S. Takakuwa Operations modeling and analysis of open pit copper mining using GPS tracking data, In Proceedings of the 2012 Winter Simulation Conference (WSC), IEEE, p. 1–12.
   Google Scholar
• P. Chaowasakoo Matching truck-and-shovel operations in open-pit mines using statistical data-dispatching strategies, match factor, and age-based maintenance, PhD thesis, Aalto University, Department of Electrical Engineering and Automation, Finland, (2017).
   Google Scholar
• A. Moradi-Afrapoli, M. Tabesh, and H. Askari-Nasab, A stochastic hybrid simulation-optimization approach towards haul fleet sizing in surface mines, Min. Technol. 128(1) (2018), pp. 9–20. doi:10.1080/25726668.2018.1473314.
   Google Scholar
• C.Z. Gurgur, K. Dagdelen, and S. Artittong, Optimization of a real-time multi-period truck dispatching system in mining operations, Int. J. Appl. Decis. Sci. 4(1) (2011), pp. 57–79.
   Google Scholar
• C.H. Ta, J.V. Kresta, J.F. Forbes, and H.J. Marquez, A stochastic optimization approach to mine truck allocation, Int. J. Surf. Min. Reclam. Environ. 19(3) (2005), pp. 162–175. doi:10.1080/13895260500128914.
   Google Scholar
• Y. Chang, H. Ren, and S. Wang, Modelling and optimizing an open-pit truck scheduling problem, Discrete Dyn. Nat. Soc. 2015 (2015), pp. 1–8. doi:10.1155/2015/745378
   Web of Science ®Google Scholar
• S.P. Upadhyay and H. Askari-Nasab, Truck-Shovel allocation optimisation: A goal programming approach, Min. Technol. 125(2) (2016), pp. 1–11. doi:10.1179/1743286315Y.0000000024.
   Google Scholar
• M. Mohtasham, H. Mirzaei-Nasirabad, H. Askari-Nasab, and B. Alizadeh, A multi-objective model for fleet allocation schedule in open-pit mines considering the impact of prioritising objectives on transportation system performance, Int. J. Min., Reclam. Environ. 35(9) (2021), pp. 1–19. doi:10.1080/17480930.2021.1949861.
   Google Scholar
• M.E.V. Matamoros and R. Dimitrakopoulos, Stochastic short-term mine production schedule accounting for fleet allocation, operational considerations and blending restrictions, Eur. J. Oper. Res. 255(3) (2016), pp. 911–921. doi:10.1016/j.ejor.2016.05.050.
   Web of Science ®Google Scholar
• M. Blom, A.R. Pearce, and P.J. Stuckey‌, Short-term scheduling of an open-pit mine with multiple objectives, Eng. Optim. 49 (5) (2017), pp. 777–795. doi:10.1080/0305215X.2016.1218002.
   Web of Science ®Google Scholar
• S. Benlaajili, F. Moutaouakkil, A. Chebak, H. Medromi, L. Deshayes, and S. Mourad Optimization of truck-shovel allocation problem in open-pit mines. in International Conference on Smart Applications and Data Analysis 2020, Jun 25; Springer, Cham.
   Google Scholar
• M. Quigley and R. Dimitrakopoulos, Incorporating geological and equipment performance uncertainty while optimising short-term mine production schedules, Int. J. Min. Reclam. Environ. 34(5) (2002), pp. 362–383. doi:10.1080/17480930.2019.1658923.
   Google Scholar
• C. Both and R. Dimitrakopoulos, Joint stochastic short term production scheduling and fleet management optimization for mining complexes, Complexes Eng. 21(4) (2020), pp. 1–27.
   Google Scholar
• F. Manríquez, H. González, and N. Morales, Short-Termopen-pit production scheduling optimizing multiple objectives accounting for shovel allocation in stockpiles, Optim. Eng. (2022), pp. 1–27.
   Web of Science ®Google Scholar
• V.A. Temeng, F.O. Otuonye, and J.O. Frendewey, A nonpreemptive goal programming approach to truck dispatching in open pit mines, Min. Res. Eng. 7(02) (1998), pp. 59–67. doi:10.1142/S0950609898000092.
   Google Scholar
• M. Mohtasham, H. Mirzaei-Nasirabad, and A. Mahmoodi Markid, Development of a goal programming model for optimization of truck allocation in open pit mines, J. Min. Env. 8(3) (2017), pp. 359–371.
   Web of Science ®Google Scholar
• H. Mirzaei-Nasirabad, M. Mohtasham, and M. Omidbad, Comparison of the various dispatching strategies for truck-shovel productivity optimization in open pit mines, Int. J. Min. Geo-Eng. 53(2) (2019), pp. 193–201.
   Google Scholar
• M. Mohtasham, H. Mirzaei-Nasirabad, and B. Alizadeh, Optimization of truck-shovel allocation in open-pit mines under uncertainty: A chance-constrained goal programming approach, Min. Technol. 130(2) (2021), pp. 81–100. doi:10.1080/25726668.2021.1916170.
   Google Scholar
• B. Forsman, E. Rönnkvist, and N. Vagenas, Truck dispatch computer simulation in Aitik open pit mine, Int. J. Surf. Min., Reclam. Environ. 7(3) (1993), pp. 117–120. doi:10.1080/17480939308547571.
   Google Scholar
• A. Arelovich, F. Masson, O. Agamennoni, S. Worrall, and E. Nebot Heuristic rule for truck dispatching in open-pit mines with local information-based decisions. In: 13th International IEEE Conference on Intelligent Transportation Systems, Funchal (2010), pp.1408–1414.
   Google Scholar
• W. Cox, T. French, M. Reynolds, and L. While A genetic algorithm for truck dispatching in mining. In GCAI. October (2017), p. 93–106.
   Google Scholar
• G.S. Bastos, Decision making applied to shift change in stochastic open-pit mining truck dispatching, IFAC Proc. 46(16) (2013), pp. 34–39.
   Google Scholar
• M. Koryagin and A. Voronov, Improving the organization of the shovel-truck systems in open-pit coal mines, Transp. Probl. 12(2) (2017), pp. 113–122. doi:10.20858/tp.2017.12.2.11.
   Web of Science ®Google Scholar
• G.I. Ahumada and O. Herzog, Application of multiagent system and Tabu search for truck dispatching in open-pit mines, In ICAART (2021), pp. 160–170.
   Google Scholar
• R.F. Alexandre, F. Campelo, and J.A. de Vasconcelos, Multi-Objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations, Learn. Nonlinear Models. 17(2) (2019), pp. 53–66. doi:10.21528/lnlm-vol17-no2-art5.
   Google Scholar
• V. Sgurev, V. Vassilev, N. Dokev, K. Genova, S. Drangajov, K. Ch, and A. Atanassov, Trasy—An automated system for real-time control of the industrial truck haulage in open-pit mines, Eur. J. Oper. Res. 43(1) (1989), pp. 44–52. doi:10.1016/0377-2217(89)90408-6.
   Web of Science ®Google Scholar
• M.X. He, J.C. Wei, X.M. Lu, and B.X. Huang, The genetic algorithm for truck dispatching problems in surface mine, Inf. Technol. J. 9(4) (2010), pp. 710–714. doi:10.3923/itj.2010.710.714.
   Google Scholar
• S.R. Patterson, E. Kozan, and P. Hyland, Energy efficient scheduling of open-pit coal mine trucks, Eur. J. Oper. Res. 262(2) (2017), pp. 759–770. doi:10.1016/j.ejor.2017.03.081.
   Web of Science ®Google Scholar
• Y. Xi and T.M. Yegulalp, Optimum dispatching algorithm for Anshan open-pit mine, in 24th APCOM, Canadian Institute of Mining, Metallurgy and Petroleum, Montreal, Quebec, Canada, 1993.
   Google Scholar
• D.K. Ahangaran, A.B. Yasrebi, A. Wetherelt, and P. Foster, Real-time dispatching modelling for trucks with different capacities in open pit mines, Arch. Min. Sci. 57 (1) (2012), pp. 39–52.
   Web of Science ®Google Scholar
• W. Morgan and L. Peterson, Determining shovel-truck productivity, Min. Eng. 20(12) (1986), pp. 76–78.
   Google Scholar
• C.N. Burt and L. Caccetta, Match factor for heterogeneous truck and loader fleets, Int. J. Min., Reclam. Environ. 21(4) (2007), pp. 262–270. doi:10.1080/17480930701388606.
   Google Scholar