In the capacitated open pit mining problem, we consider the sequential extraction of blocks in order to maximize the total discounted profit under an extraction capacity during each period of the horizon. We propose a formulation closely related to the resource-constrained project scheduling problem(RCPSP) where the genotype representation of the solution is based on a priority value encoding. We use a GRASP procedure to generate an initial population (swarm) evolving according to a particle swarm procedureto search the feasible domain of the representations. Numerical results are introduced to analyze the impact of the different parameters of the procedures.
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References
Cacetta, L., Kelsey, P., Giannini, L.M. (1998), “Open pit mine production scheduling”, Computer Applications in the Mineral Industries International Symposium (3rd Regional APCOM), Austral. Inst. Min. Metall. Publication Series, 5: 65-72.
Dagdelen, K., Johnson, T.B. (1986), “Optimum open pit mine production scheduling by lagrangian parameterization”, Proceedings of the 19 th APCOM Symposium of the Society of Mining Engineers (AIME), 127-142.
Denby, B., Schofield, D. (1995), “The use of genetic algorithms in underground mine scheduling”, Proceedings 25 th APCOM Symposium of the Society of Mining Engineers (AIME), 389-394.
Denby, B., Schofield, D., Bradford, S. (1991), “Neural network applications in mining engineering”, Department of Mineral Resources Engineering Mgzine, University of Nootingham, 13-23.
Eberhart, R.C., Shi, Y. (2000), “Comparing inertia weights and construction factors in particle swarm optimization” Proceedings of the Congress on Evolutionary Computation, 84-88.
François-Bongarçon, D.M., Guibal, D. (1984), “Parametization of optimal designs of an open pit beginning a new phase of research”, Transactions SME, AIME, 274: 1801-1805.
Gershon, M. (1983), “Mine scheduling optimization with mixed integer programming”, Mining Engineering, 35: 351-354.
Gershon, M. (1987), “Heuristic approaches for mine planning and production scheduling”, International Journal of Mining and Geological Engineering, 5: 1-13.
Hartmann, S. (1998), “A competitive genetic algorithm for the resourceconstrained project scheduling”, Naval Research Logistics, 456: 733-750.
Kennedy, J., Eberhart, R.C. (1995), “Particle swarm optimization”, Proceedings of the IEEE International Conference on Neural Networks, IV: 1942-1948.
Lerchs, H., Grossman, I.F. (1965), “Optimum design for open pit mines”, CIM Bulletin, 58: 47-54.
Matheron, G. (1975), “Le paramétrage des contours optimaux”, Technical report no. 403, Centre de Géostatistiques, Fontainebleau, France.
Paquet, U., Engelbrecht, A.P. (2003), “A new particle swarm optimiser for linearly constrained optimization”, Proceedings of the 2003 Congress on Evolutionary Computation, 227-233.
Picard, J.C. (1976), “Maximal closure of a graph and applications to combinatorial problems”, Management Science, 22: 1268-1272.
Shi, Y., Eberhart, R.C. (1998), “A modified particle swarm optimizer”, Proceedings of the IEEE Congress on Evolutionary Computation, Piscataway, New Jersey, 69-73.
Tolwinski, B., Underwood, R. (1996), “A scheduling algorithm for open pitmines”, IMA Journal of Mathematics Applied in Business & Industry, 7: 247-270.
Whittle, J. (1998), “Four-X user manual”, Whittle Programming Pty Ltd, Melbourne, Australia.
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Ferland, J.A., Amaya, J., Djuimo, M.S. (2007). Application of a Particle Swarm Algorithm to the Capacitated Open Pit Mining Problem. In: Mukhopadhyay, S.C., Gupta, G.S. (eds) Autonomous Robots and Agents. Studies in Computational Intelligence, vol 76. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73424-6_15
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