Document Type : Original Research Paper

Authors

1 Department of mining engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

2 Department of mining engineering, Hamedan University of Technology, Hamedan,

3 Department of mining engineering, Faculty of Engineering, Urmia University of Technology, Urmia, Iran

Abstract

The production cycle in open-pit mines includes the drilling, blasting, loading, and haulage. Since loading and haulage account for a large part of the mining costs, it is very important to optimize the transport fleet from the economic viewpoint. Simulation is one of the most widely used methods in the field of fleet design. However, it is unable to propose an optimized scenario for which the appropriate metaheuristic method should be employed. This paper considers the Sungun copper mine as the case study, and attempts to find the most feasible transportation arrangement. In the first step, in this work, we compare the flexible dispatching with the fixed allocation methods using the Arena software. Accordingly, the use of flexible dispatching reveals the increase in the production rate (20%) and productivity (25%), and the decrease (20%) in the idle time. The firefly metaheuristic algorithm used in the second step shows that the combined scenario of the 35-ton and 100-ton trucks is the most suitable option in terms of productivity and cost. In another attempt, comparing different heterogeneous truck fleets, we have found that the scenarios 35-100 and 35-60-100-144 increase the production rate by 39% and 49%, respectively. Also, in both scenarios, the production cost decreases by 11% and 21%, respectively.

Keywords

[1]. Altiok, T. and Melamed, B. (2010). Simulation modeling and analysis with Arena. Elsevier.
[2]. Azadi, N., Monjezi, M. and Ataeepour, M. (2015). EFFICIENCY IMPROVEMENT OF THE SONGUN COPPER MINE FLEET USING SIMULATION TECHNIQUE. Journal of Modeling in Engineering. 12 (39): 99-110.
[3]. Baafi, E. and Ataeepour, M. (1996). Simulation of a truck-shovel system using Arena. In Proceeding of the 26th International Symposium on the Application of Computers and Operations Research in the Mineral Industries (APCOM) (pp. 153-159).
[4]. Bakhtavar, E., Sadiq, R. and Hewage, K. (2021). Optimization of Blasting-Associated Costs in Surface Mines Using Risk-based Probabilistic Integer Programming and Firefly Algorithm. Natural Resources Research. 30 (6): 4789-4806.
[5]. Banks, J. (2005). Discrete event system simulation. Pearson Education India.
[6]. Bonates, E. and Lizotte, Y. (1988). A computer simulation model to evaluate the effect of dispatching. International Journal of Surface Mining, Reclamation and Environment. 2 (2): 99-104.
[7]. Castillo, D. and Cochran, J.K. (1987). A microcomputer approach for simulating truck haulage systems in open pit mining. Computers in Industry. 8 (1): 37-47.
[8] Chaowasakoo, P., Seppälä, H., Koivo, H. and Zhou, Q. (2017). Improving fleet management in mines: The benefit of heterogeneous match factor. European journal of operational research. 261 (3): 1052-1065.
[9]. Clarke, M.P., Denby, B. and Schofield, D. (1990). Decision making tools for surface mine equipment selection. Mining Science and Technology. 10 (3): 323-335.
[10]. Fister, I., Fister Jr, I., Yang, X.S. and Brest, J. (2013). A comprehensive review of firefly algorithms. Swarm and Evolutionary Computation. 13: 34-46.
[11]. Hashemi, A.S. and Sattarvand, J. (2015). Simulation based investigation of different fleet management paradigms in open pit mines-a case study of Sungun copper mine. Archives of Mining Sciences. 60 (1).
[12]. Jamil, A., Abdallah, B.N. and Leksono, V.A. (2021). Firefly Algorithm for Multi-type Vehicle Routing Problem. In Journal of Physics: Conference Series (Vol. 1726, No. 1, p. 012006). IOP Publishing.
[13]. Jaoua, A., Gamache, M. and Riopel, D. (2012). Specification of an intelligent simulation-based real time control architecture: Application to truck control system. Computers in Industry. 63 (9): 882-894.
[14]. Kennedy, J. and Eberhart, R. Particle swarm optimization. InProceedings of ICNN’95-International Conference on Neural Networks 1995 Nov 27 (Vol. 4, pp. 1942–1948). IEEE. View Article.
[15]. Khan, W.A., Hamadneh, N.N., Tilahun, S.L. and Ngnotchouye, J.M. (2016). A review and comparative study of firefly algorithm and its modified versions. Optimization Algorithms-Methods and Applications, 281-313.
[16]. Mena, R., Zio, E., Kristjanpoller, F. and Arata, A. (2013). Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints. International Journal of mining science and Technology. 23 (1): 113-119.
[17]. Ministry of Industries and Mines, Iran Mining Development and Renovation Organization, National Iranian Copper Industries Company Sungun Copper Project, Introduction to Sungun Copper Mine, Supervision Unit, April 2003.
[18]. Mohtasham, M., Mirzaei-Nasirabad, H., Askari-Nasab, H. and Alizadeh, B. (2021). Truck fleet size selection in open-pit mines based on the match factor using a MINLP model. Mining Technology, 1-17.
[19]. Negnevitsky, M. and Intelligence, A. (2005). A guide to intelligent systems. Artificial Intelligence, 2nd edition, pearson Education.
[20]. Palit, S., Sinha, S.N., Molla, M.A., Khanra, A. and Kule, M. (2011, September). A cryptanalytic attack on the knapsack cryptosystem using binary firefly algorithm. In 2011 2nd International conference on computer and communication technology (ICCCT-2011) (pp. 428-432). IEEE.
[21]. Panagiotou, G.N. (1999). Discrete mine system simulation in Europe. International Journal of Surface Mining, Reclamation and Environment. 13 (2): 43-46.
[22]. Pegden, C.D. and Davis, D.A. (1992, December). Arena: a SIMAN/Cinema-based hierarchical modeling system. In Proceedings of the 24th conference on Winter simulation (pp. 390-399).
[23]. Rist, K.A. (1961). Computer Simulation for Solution of a Mine Transportation Problem. Mining World. 23 (13): 19-22.
[24]. Sadowski, R.P., Kelton, W.D. and Sadowski, R.P. (1998). Simulation with ARENA. McGraw-Hill.
[25]. Sturgul, J.R. (2001). Modeling and simulation in mining-Its time has finally arrived. Simulation. 76 (5): 286-288.
[26]. Temeng, V.A. (1997). A computerized model for truck dispatching in open pit mines. Michigan Technological University.
[27]. Tilahun, S.L. and Ong, H.C. (2015). Prey-predator algorithm: a new metaheuristic algorithm for optimization problems. International Journal of Information Technology & Decision Making. 14 (06): 1331-1352.
[28]. Upadhyay, S.P. and Askari-Nasab, H. (2016). Uncertainty based short term planning in open pit mines–simulation optimization approach. MOL Annual Report Seven 2015/2016 (ISBN: 978-1-55195-367-0), 7, 120-148.
[29]. Upadhyay, S., Tabesh, M., Badiozamani, M. and Askari-Nasab, H. (2019, December). A Simulation Model for Estimation of Mine Haulage Fleet Productivity. In International Symposium on Mine Planning & Equipment Selection (pp. 42-50). Springer, Cham.
[30]. Yang, X.S. and He, X. (2013). Firefly algorithm: recent advances and applications. International journal of swarm intelligence, 1(1), 36-50.
[31]. Yang, X.S. (2010). Nature-inspired metaheuristic algorithms. Luniver press.
[32]. Yang, X.S. (2010). Firefly algorithm, stochastic test functions and design optimisation. International journal of bio-inspired computation. 2 (2): 78-84.
[33]. Yeganejou, M., Badiozamani, M., Moradi-Afrapoli, A. and Askari-Nasab, H. (2021). Integration of simulation and dispatch modelling to predict fleet productivity: an open-pit mining case. Mining Technology, 1-13.
[34]. Zeng, W., Baafi, E.Y., Walker, D.K. and Cai, D. (2016). A 3D discrete event simulation model of a truck-shovel network system.
[35]. Zhang, X., Chen, L., Ai, Y., Tian, B., Cao, D. and Li, L. (2021, September). Scheduling of Autonomous Mining Trucks: Allocation Model Based Tabu Search Algorithm Development. In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) (pp. 982-989). IEEE.