Sustainable open pit fleet management system: integrating economic and environmental objectives into truck allocation

References

• Ahangaran DK, Yasrebi AB, Wetherelt A, Foster P. 2012. Real –time dispatching modelling for trucks with different capacities in open pit mines. Arch Min Sci. 57(1). doi:10.2478/v10267-012-0003-8.
   Web of Science ®Google Scholar
• Aksoy A, Küçükoğlu İ, Ene S, Öztürk N. 2014. Integrated emission and fuel consumption calculation model for green supply chain management. Proc Soc Behav Sci. 109:1106–1109. doi:10.1016/j.sbspro.2013.12.595.
   Google Scholar
• Alarie S, Gamache M. 2002. Overview of solution strategies used in truck dispatching systems for open pit mines. Int J Surf Mining, Reclamation Environ. 16(1):59–76. doi:10.1076/ijsm.16.1.59.3408.
   Google Scholar
• Alexandre RF, Campelo F, Vasconcelos JA. 2019. Multi-objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations. Learn Nonlin Mod. 17(2):53–66. doi:10.21528/lnlm-vol17-no2-art5.
   Google Scholar
• Alinaghian M, Naderipour M. 2016. A novel comprehensive macroscopic model for time-dependent vehicle routing problem with multi-alternative graph to reduce fuel consumption: A case study. Comput Ind Eng. 99:210–222. doi:10.1016/j.cie.2016.07.029.
   Web of Science ®Google Scholar
• Both C, Dimitrakopoulos R. 2020. Joint stochastic short-term production scheduling and fleet management optimization for mining complexes. Optimiz Eng. 21(4):1717–1743. doi:10.1007/s11081-020-09495-x.
   Web of Science ®Google Scholar
• Gurgur CZ, Dagdelen K, Artittong S. 2011. Optimisation of a real-time multi-period truck dispatching system in mining operations. Int J Appl Dec Sci. 4(1):57–79. doi:10.1504/IJADS.2011.038091.
   Google Scholar
• Levinson Z, Dimitrakopoulos R. 2020. Simultaneous stochastic optimisation of an open-pit gold mining complex with waste management. Int J Min Reclam Environ. 34(6):415–429. doi:10.1080/17480930.2019.1621441.
   Web of Science ®Google Scholar
• Mane A, Djordjevic B, Ghosh B. 2021. A data-driven framework for incentivising fuel-efficient driving behaviour in heavy-duty vehicles. Transport Res Part D: Transp Env. 95:102845. doi:10.1016/j.trd.2021.102845.
   Web of Science ®Google Scholar
• Mena R, Zio E, Kristjanpoller F, Arata A. 2013. Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints. Int J Minin Sci Techn. 23(1):113–119. doi:10.1016/j.ijmst.2013.01.017.
   Google Scholar
• Mohtasham M, Mirzaei-Nasirabad H, Alizadeh B. 2021. Optimization of truck-shovel allocation in open-pit mines under uncertainty: a chance-constrained goal programming approach. Min Technol. 130(2):81–100. doi:10.1080/25726668.2021.1916170.
   Google Scholar
• Mohtasham M, Mirzaei-Nasirabad H, Askari-Nasab H, Alizadeh B. 2021a. 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(10):709–727. doi:10.1080/17480930.2021.1949861.
   Web of Science ®Google Scholar
• Mohtasham M, Mirzaei-Nasirabad H, Askari-Nasab H, Alizadeh B. 2021b. Truck fleet size selection in open-pit mines based on the match factor using a MINLP model. Min Technol. 130(3):159–175. doi:10.1080/25726668.2021.1919374.
   Google Scholar
• Mohtasham M, Mirzaei-Nasirabad H, Askari-Nasab H, Alizadeh B. 2022. Multi-stage optimization framework for the real-time truck decision problem in open-pit mines: a case study on sungun copper mine. Int J Min Reclam Environ. 36(7):461–491. doi:10.1080/17480930.2022.2067709.
   Web of Science ®Google Scholar
• Montiel L, Dimitrakopoulos R. 2015. Optimizing mining complexes with multiple processing and transportation alternatives: An uncertainty-based approach. Eur J Oper Res. 247(1):166–178. doi:10.1016/j.ejor.2015.05.002.
   Web of Science ®Google Scholar
• Moradi Afrapoli A, Askari-Nasab H. 2019. Mining fleet management systems: a review of models and algorithms. Int J Min Reclam Environ. 33(1):42–60. doi:10.1080/17480930.2017.1336607.
   Web of Science ®Google Scholar
• Moradi Afrapoli A, Tabesh M, Askari-Nasab H. 2019. A multiple objective transportation problem approach to dynamic truck dispatching in surface mines. Eur J Oper Res. 276(1):331–342. doi:10.1016/j.ejor.2019.01.008.
   Web of Science ®Google Scholar
• Moradi Afrapoli A, Tabesh M, Askari-Nasab H. 2019. A stochastic hybrid simulation-optimization approach towards haul fleet sizing in surface mines. Min Technol. 128(1):9–20. doi:10.1080/25726668.2018.1473314.
   Web of Science ®Google Scholar
• Moradi Afrapoli A, Upadhyay S, Askari-Nasab H. 2021. Truck dispatching in surface mines -Application of fuzzy linear programming. Journal of the Southern African Institute of Mining and Metallurgy. 121(9):505–512. doi:10.17159/2411-9717/522/2021 .
   Web of Science ®Google Scholar
• Ozdemir B, Kumral M. 2019. Simulation-based optimization of truck-shovel material handling systems in multi-pit surface mines. Simul Model Pract Theory. 95:36–48. doi:10.1016/j.simpat.2019.04.006.
   Web of Science ®Google Scholar
• Peralta S, Sasmito AP, Kumral M. 2016. Reliability effect on energy consumption and greenhouse gas emissions of mining hauling fleet towards sustainable mining. J. Sust Min. 15(3):85–94. doi:10.1016/j.jsm.2016.08.002.
   Google Scholar
• Saliba Z, Dimitrakopoulos R. 2019. Simultaneous stochastic optimization of an open pit gold mining complex with supply and market uncertainty. Min Technol. 128(4):216–229. doi:10.1080/25726668.2019.1626169.
   Google Scholar
• Souza MJ, Coelho IM, Ribas S, Santos HG, Merschmann LHDC. 2010. A hybrid heuristic algorithm for the open-pit-mining operational planning problem. Eur J Oper Res. 207(2):1041–1051. doi:10.1016/j.ejor.2010.05.031.
   Web of Science ®Google Scholar
• Ta CH, Ingolfsson A, Doucette J. 2013. A linear model for surface mining haul truck allocation incorporating shovel idle probabilities. Eur J Oper Res. 231(3):770–778. doi:10.1016/j.ejor.2013.06.016.
   Web of Science ®Google Scholar
• Ta CH, Kresta JV, Forbes JF, Marquez HJ. 2005. A stochastic optimization approach to mine truck allocation. Int J Surf Mining Reclamation Environ. 19(3):162–175. doi:10.1080/13895260500128914.
   Google Scholar
• Topal E, Ramazan S. 2010. A new MIP model for mine equipment scheduling by minimizing maintenance cost. Eur J Oper Res. 207(2):1065–1071. doi:10.1016/j.ejor.2010.05.037.
   Web of Science ®Google Scholar
• Walnum HJ, Simonsen M. 2015. Does driving behavior matter? An analysis of fuel consumption data from heavy-duty trucks. Transport Res Part D: Trans Env. 36:107–120. doi:10.1016/j.trd.2015.02.016.
   Web of Science ®Google Scholar
• Winebrake JJ, Green EH. 2017. Environmental policy, decision making, and rebound effects in the U.S. trucking sector. Res Transport Busin Manag. 23:54–63. doi:10.1016/j.rtbm.2017.02.008.
   Web of Science ®Google Scholar
• Yeganejou M, Badiozamani M, Moradi-Afrapoli A, Askari-Nasab H. 2022. Integration of simulation and dispatch modelling to predict fleet productivity: an open-pit mining case. Min Technol. 131(2):67–79. doi:10.1080/25726668.2021.2001255.
   Google Scholar
• Zeng W, Baafi E, Walker D. 2019. A simulation model to study bunching effect of a truck-shovel system. Int J Min Reclam Environ. 33(2):102–117. doi:10.1080/17480930.2017.1348284.
   Web of Science ®Google Scholar
• Zhang L, Xia X. 2015. An integer programming approach for truck-shovel dispatching problem in open-pit mines. Energ Proced. 75:1779–1784. doi:10.1016/j.egypro.2015.07.469.
   Google Scholar