Goal programming for sizing and allocation of a fleet of trucks in a mining company
DOI:
https://doi.org/10.26439/interfases2019.n012.4639Keywords:
Truck allocation, mining, linear programming, goal programmingAbstract
Decision making in mining is a complicated process. Decisions regarding the sizing and allocation of the fleet of trucks to different mines, considering the compliance with production and the total objective cost, are of paramount importance to mining companies as this directly affects their profits. This document presents a model of goal programming (based on linear programming) to optimize mining operations in underground mining taking into account three goals: (a) To minimize deviations from the target production of different minerals, (b) to minimize the surplus of the total designated operating cost and (c) to maximize the use of concentrator plants’ maximum capacity. The model determines the number of trucks needed and provides the optimal allocation to each mine while addressing the goals and limitations of the mining operation. The proposed model was validated using real data from a Peruvian mining company.
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References
Alvarado Boirivant, J. (2009). La programación lineal aplicación de las pequeñas y medianas empresas. Reflexiones, 88(1), pp. 89-105.
Bajany, D. M., Xia, X., y Zhang, L. (2017). A MILP Model for Truck-shovel scheduling to minimize fuel consumption. Energy Procedia, 105, pp. 2739-2745.
Bazaraa, M. S., Jarvis, J. J., y Sherali, H. D. (2011). Linear programming and network flows. Hoboken, Estados Unidos: John Wiley & Sons.
Burt, C., Caccetta, L., Hill, S., Welgama, P., Zerger, A., y Argent, R. M. (2005). Models for mining equipment selection. International Congress Modeling Simulation. Modelling and Simulation Society of Australia and New Zealand, pp. 1730-1736.
Charnes, A., y Stredy, A. (1966). The attainment of organizational goals through the appropriate selection of sub-unit goals. Operational Research and the Social Sciences. Tavistock Publications.
Crovo, A. S., Martín, C. O. y Rojas, L. P. (2007). Modelos de programación entera para un problema de programación de horarios para universidades. Revista Chilena de Ingeniería.
Derigs, U. (2009). Optimization and operations research (volume I). Oxford, Inglaterra: EOLSS Publications.
Elbrond, J., y Soumis, F. (1987). Towards integrated production planning and truck dispatching in open pit mines. International Journal of Surface Mining, pp. 1-6.
Hillier, F., y Lieberman, G. (2014). Introduction to operations research (10th ed.). New York: Mcgraw Hill Education.
Kornbluth, J. S. H. (1973). A survey of goal programming. Omega, 1(2), pp. 193-205.
Lawrence, O. (2017). Linear programming as a tool for water resources management. International Journal of Constructive Research in Civil Engineering, 3(4), pp. 30-47.
LCG Energy Management Group. (2009). Investigation of current research related to the reduction of energy usage in mines through recycling, reuse, and other means.
Matousek, J., y Gärtner, B. (2007). Understanding and using linear programming. Berlín: Springer Science & Business Media.
McDill, M. E. (1999). Forest Resource Management. Recuperado de https://www.courses.psu.edu/for/for466w_mem14/PDFs/
Nehring, M., Topal, E., y Knights, P. (2010). Dynamic short term production scheduling and machine allocation in underground mining using mathematical programming. Mining Technology, 119(4), pp. 212-220.
Sahoo, L. K., Bandyopadhyay, S., y Banerjee, R. (2014). Benchmarking energy consumption for dump trucks in mines. Applied Energy, 113, pp. 1382-1396.
Ta, C. H., Ingolfsson, A., y Doucette, J. (2013). A linear model for surface mining haul truck allocation incorporating shovel idle probabilities. European Journal of Operational Research, 231(3), pp. 770-778.
Ta, C. H., Kresta, J. V., Forbes, J. F., y Marquez, H. J. (2005). A stochastic optimization approach to mine truck allocation. International Journal of Mining, Reclamation and Environment, 19(3), pp. 162-175.
Taha, H. A. (2004). Investigación de operaciones. México: Pearson Educación.
Tamiz, M., Jones, D., y Romero, C. (1998). Goal programming for decision making: An overview of the current state-of-the-art. European Journal of Operational Research, 111(3), pp. 569-581.
Temeng, V. A., Francis, O. O., y Frendewey, Jr., J. O. (1997). Real-time truck dispatching using a transportation algorithm. International Journal of Surface Mining, Reclamation and Environment. 11(4), pp. 203-207.
Upadhyay, S. P., y Askari-Nasab, H. (2016). Truck-shovel allocation optimisation: a goal programming approach. Mining Technology, 125(2), pp. 82-92.
Zhang, L., y Xia, X. (2015). An integer programming approach for truck-shovel dispatching problem in open-pit mines. Energy Procedia, 75, pp. 1779-1784.
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Last updated 03/05/21
