Decision Support for Ore Transportation in Mining Enterprises – a Systematic Literature Review
DOI:
https://doi.org/10.24425/mper.2025.156143Abstract
Excavated material transportation is crucial in mining operations, requiring optimal efficiency. Since the early 2000s, various aspects of transportation network optimization have been researched, often producing methods with overlapping objectives and outcomes. This work consolidates and analyzes existing methods and artifacts related to decision support for optimizing ore transportation networks. A systematic literature review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, was conducted using sources such as Scopus, Web of Science, and Google Scholar. Out of 170 initial research papers, 46 were selected for detailed analysis. The review highlights the current state of decision support in ore transportation, focusing on supported decisions, optimized processes, and applied methods. It also identifies research gaps and future trends in this field.References
Abolghasemian, M., Ghane Kanafi, A., & Daneshmandmehr, M. (2020). A two-phase simulation-based optimization of hauling system in open-pit mine. Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies), 13(4), 705–732.
Aghajani Bazzazi, A., Osanloo, M., & Karimi, B. (2011a). A new fuzzy multi criteria decision making model for open pit mines equipment selection. Asia-Pacific Journal of Operational Research, 28(3), 279–300.
Aghajani Bazzazi, A., Osanloo, M., & Karimi, B. (2011b). Deriving preference order of open pit mines equipment through MADM methods: Application of modified VIKOR method. Expert Systems with Applications, 38(3), 2550–2556.
Ahangaran, D.K., Yasrebi, A.B., Wetherelt, A., & Foster, P. (2012). Real–time dispatching modelling for trucks with different capacities in open pit mines. Archives of Mining Sciences, 57(1).
Alford, C., Brazil, M., & Lee, D.H. (2007). Optimisation in underground mining. In Handbook of operations research in natural resources (pp. 561–577).
Boston, MA: Springer US. Bardzinski, P., Jurdziak, L., Kawalec, W., & Krol, R. (2020). Copper ore quality tracking in a belt conveyor system using simulation tools. Natural Resources Research, 29(2), 1031–1040.
Bastos, G.S. (2013). Decision making applied to shift change in stochastic open-pit mining truck dispatching. IFAC Proceedings Volumes, 46(16), 34–39.
Blachowski, J., Górniak-Zimroz, J., Milczarek, W., & Pactwa, K. (2017). Applications of geomatics in underground mining. International Multidisciplinary Scientific GeoConference: SGEM, 17, 799–810.
Brazil, M., & Thomas, D.A. (2007). Network optimization for the design of underground mines. Networks: An International Journal, 49(1), 40–50.
Campeau, L.P., & Gamache, M. (2020). Short-term planning optimization model for underground mines. Computers & Operations Research, 115, 104642.
Cao, X., Li, P., & Duan, Y. (2021). Joint decision-making model for production planning and maintenance of fully mechanized mining equipment. IEEE Access, 9, 46960–46974.
Chen, C., & Shi, L. (2017, March). Simulating and optimizing of tramcar transportation attempter in open pit mine. In 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017) (pp. 29–33). Atlantis Press.
Eivazy, H., & Askari-Nasab, H. (2012). A hierarchical open-pit mine production scheduling optimisation model. International Journal of Mining and Mineral Engineering, 4(2), 89–115.
Elevli, B.* & Demirci, A. (2004). Multicriteria choice of ore transport system for an underground mine: application of PTOMETHEE methods. Journal of the Southern African Institute of Mining and Metallurgy, 104(5), 251–256.
Ghasvareh, M.A., Safari, M., & Nikkhah, M. (2019). Haulage system selection for Parvadeh Coal Mine using multi-criteria decision making methods. Mining Science, 26, 69–90.
Goodfellow, R., & Dimitrakopoulos, R. (2017). Simultaneous stochastic optimization of mining complexes and mineral value chains. Mathematical Geosciences, 49(3), 341–360.
Gul, M., Ak, M.F., & Guneri, A.F. (2019). Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry. Journal of Safety Research, 69, 135–153.
Haidar, A., Naoum, S., Howes, R., & Tah, J. (1999). Genetic algorithms application and testing for equipment selection. Journal of Construction Engineering and Management, 125(1), 32–38.
Jakkula, B., Govinda Raj, M., & Murthy Ch.S.N. (2020). Maintenance management of load haul dumper using reliability analysis. Journal of Quality in Maintenance Engineering, 26(2), 290–310.
Jovanovic, S., Gligoric, Z., Beljic, C., Gluscevic, B., & Cvijovic, C. (2014). Fuzzy model for selection of underground mine development system in a bauxite deposit. Arabian Journal for Science and Engineering, 39(6), 4529–4539.
Jurdziak, L., Kawalec, W., & Krol, R. (2019). Guidelines for Ore Tracking System in the Complex Underground Transportation Got from the DISIRE Project. In IOP Conference Series: Earth and Environmental Science (Vol. 221, No. 1, p. 012101). IOP Publishing.
Karami, A., & Szymanski, J. (1997). A simulation model of an underground mine haulage system. Mineral Resources Engineering, 6(4), 229–238.
Kozlowski, T., Michalak, A., Zimroz, R., Sliwinski, P., & Kaniewski, T. (2019, November). An algorithm for determining unloading cycles in dump truck. In IOP Conference Series: Earth and Environmental Science, 362(1), 012111. IOP Publishing.
Kuznetsov, D., & Kosolapov, A. (2022). Dynamic of performance of open-pit dump trucks in ore mining in severe climatic environment. Transportation Research Procedia, 63, 1042–1048.
Lashgari, A., Yazdani–Chamzini, A., Fouladgar, M.M., Zavadskas, E.K., Shafiee, S., & Abbate, N. (2012). Equipment selection using fuzzy multi criteria decision making model: key study of Gole Gohar iron min. Engineering economics, 23(2), 125–136.
Li, N., Feng, S., Ye, H., Wang, Q., Jia, M., Wang, L., ... & Chen, D. (2021). Dispatch optimization model for haulage equipment between stopes based on mine short-term resource planning. Metals, 11(11), 1848.
Lin, H., Liu, P., Li, W., Zhang, L.P., & Ji, Y.Z. (2012). Construction of digital mine and key technologies. Advanced Materials Research, 524, 413–420.
Ma, W., Du, Y., Liu, X., & Shen, Y. (2022). Literature review: Multi-criteria decision-making method application for sustainable deep-sea mining transport plans. Ecological Indicators, 140, 109049.
Matsui, K. (2009). Underground mining transportation systems. Civil Engineering, 2(5), 285.
Meng, C., Nageshwaraniyer, S.S., Maghsoudi, A., Son, Y.J., & Dessureault, S. (2013). Data-driven modeling and simulation framework for material handling systems in coal mines. Computers & Industrial Engineering, 64(3), 766–779.
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Bmj, 339.
Navidi, S., Motamedi, M., Aghsami, A., & Jolai, F. (2023). AG/M/C//M queueing model for revenue management of shovel-truck systems in an open-pit mine considering carbon emission, a case study. International Journal of Management Science and Engineering Management, 18(2), 88–103.
Nehring, M., Topal, E., & Knights, P. (2010). Dynamic short term production scheduling and machine allocation in underground mining using mathematical programming. Mining Technology, 119(4), 212–220.
Nguyen, D.K., & Bui, X.N. (2015). A real-time regulation model in multi-agent decision support system for open pit mining. In Proceedings of the 12th International Symposium Continuous Surface Mining-Aachen 2014 (pp. 255–262). Cham: Springer International Publishing.
Osanloo, M., & Paricheh, M. (2020). In-pit crushing and conveying technology in open-pit mining operations: a literature review and research agenda. International Journal of Mining, Reclamation and Environment, 34(6), 430–457.
Paduraru, C., & Dimitrakopoulos, R. (2019). Responding to new information in a mining complex: Fast mechanisms using machine learning. Mining Technology.
Pascual, R., Martínez, A., & Giesen, R. (2013). Joint optimization of fleet size and maintenance capacity in a fork-join cyclical transportation system. Journal of the Operational Research Society, 64(7), 982–994.
Patterson, S.R., Kozan, E., & Hyland, P. (2016). An integrated model of an open-pit coal mine: improving energy efficiency decisions. International Journal of Production Research, 54(14), 4213–4227.
Patterson, S.R., Kozan, E., & Hyland, P. (2017). Energy efficient scheduling of open-pit coal mine trucks. European Journal of Operational Research, 262(2), 759–770.
Pimentel, B.S., Gonzalez, E.S., & Barbosa, G.N. (2016). Decision-support models for sustainable mining networks: fundamentals and challenges. Journal of Cleaner Production, 112, 2145–2157.
Qinghua, G.U., Caiwu, L.U., Jinping, G.U.O., & Shigun, J.I.N.G. (2010). Dynamic management system of ore blending in an open pit mine based on GIS/GPS/GPRS. Mining Science and Technology (China), 20(1), 132–137.
Rakhmangulov, A., Burmistrov, K., & Osintsev, N. (2022). Selection of open-pit mining and technical system’s sustainable development strategies based on MCDM. Sustainability, 14(13), 8003.
Salama, A., Greberg, J., & Schunnesson, H. (2014). The use of discrete event simulation for underground haulage mining equipment selection. International Journal of Mining and Mineral Engineering, 5(3), 256–271.
Samanta, B., Sarkar, B., & Mukherjee, S.K. (2002). Selection of opencast mining equipment by a multi-criteria decision-making process. Mining Technology, 111(2), 136–142.
Shamsi, M., Pourrahimian, Y., & Rahmanpour, M. (2022). Optimisation of open-pit mine production scheduling considering optimum transportation system between truck haulage and semi-mobile in-pit crushing and conveying. International Journal of Mining, Reclamation and Environment, 36(2), 142-158.
Sitorus, F., Cilliers, J.J., & Brito-Parada, P.R. (2019). Multi-criteria decision making for the choice problem in mining and mineral processing: Applications and trends. Expert systems with applications, 121, 393–417.
Souza, M.J., Coelho, I.M., Ribas, S., Santos, H.G., & Merschmann, L.H.D.C. (2010). A hybrid heuristic algorithm for the open-pit-mining operational planning problem. European Journal of Operational Research, 207(2), 1041–1051.
Stefaniak, P., Śliwiński, P., Duda, N., & Jachnik, B. (2020, November). Multidimensional Analysis of SCADA Stream Data for Estimating the Energy Efficiency of Mining Transport. In International Conference on Computational Collective Intelligence (pp. 314–325). Cham: Springer International Publishing.
Stefaniak, P., Wodecki, J., & Zimroz, R. (2016, September). Maintenance management of mining belt conveyor system based on data fusion and advanced analytics. In International Congress on Technical Diagnostics (pp. 465–476). Cham: Springer International Publishing.
Stepanova, I.V., Aksyonov, K.A., & Aksyonova, O.P. (2022, April). Hybrid simulation-agent modeling of ore mining and transportation process. In American Institute of Physics Conference Series (Vol. 2425, No. 1, p. 130004).
Subtil, R.F., Silva, D.M., & Alves, J.C. (2011, September). A practical approach to truck dispatch for open pit mines. In 35Th APCOM symposium (pp. 24–30).
Temkin, I.O., Myaskov, A.V., Deryabin, S.A., & Rzazade, U.A. (2020). Digital twins and modeling of the transporting-technological processes for on-line dispatch control in open pit mining. Eurasian Mining, 2, 55–58.
Tubis, A., Werbińska-Wojciechowska, S., & Wroblewski, A. (2020). Risk assessment methods in mining industry – a systematic review. Applied Sciences, 10(15), 5172.
Upadhyay, S.P., & Askari-Nasab, H. (2018). Simulation and optimization approach for uncertainty-based short-term planning in open pit mines. International Journal of Mining Science and Technology, 28(2), 153–166.
Upadhyay, S.P., Askari-Nasab, H., Tabesh, M., & Badiozamani, M.M. (2015, May). Simulation and optimization in open pit mining. In Proceedings of the Application of Computers and Operations Research in the Mineral Industry – Proceedings of the 37th International Symposium APCOM.
Vasquez, O.C., Sepúlveda, J.M., & Córdova, F. (2011). Modeling and optimization of vehicle operations in underground copper mining. Rem: Revista Escola de Minas, 64, 365–371.
Wang, Z., Wang, J., Zhao, M., Guo, Q., Zeng, X., Xin, F., & Zhou, H. (2022). Truck Dispatching Optimization Model and Algorithm Based on 0-1 Decision Variables. Mathematical Problems in Engineering, 2022(1), 5887672.
Wodecki, J., Stefaniak, P., Polak, M., & Zimroz, R. (2016, September). Unsupervised anomaly detection for conveyor temperature SCADA data. In International Conference on Condition Monitoring of Machinery in Non-Stationary Operation (pp. 361–369). Cham: Springer International Publishing.
Xiwen, F., & Zhongling, Z. (2010, April). Research and application on visual simulation of production logistics system of coal mine. In 2010 2nd IEEE International Conference on Information Management and Engineering (pp. 445–449). IEEE.
Yang, S., Wang, J., Li, M., & Yue, H. (2022). Research on intellectualized location of coal gangue logistics nodes based on particle swarm optimization and quasi-newton algorithm. Mathematics, 10(1), 162.
Yao, J., Wang, Z., Chen, H., Hou, W., Zhang, X., Li, X., & Yuan, W. (2023). Open-pit mine truck dispatching system based on dynamic ore blending decisions. Sustainability, 15(4), 3399.
Yavuz, M., Iphar, M., & Once, G. (2008). The optimum support design selection by using AHP method for the main haulage road in WLC Tuncbilek colliery. Tunnelling and Underground Space Technology, 23(2), 111–119.
Zimroz, R., Stefaniak, P.K., Bartelmus, W., & Hardygora, M. (2014, September). Novel techniques of diagnostic data processing for belt conveyor maintenance. In Proceedings of the 12th International Symposium Continuous Surface Mining-Aachen 2014 (pp. 31–40). Cham: Springer International Publishing.
