An MILP approach to Multi-location, Multi-Period Equipment Selection for Surface Mining with Case Studies

نویسندگان

  • Christina Burt
  • Louis Caccetta
  • Palitha Welgama
  • Leon Fouché
چکیده

In the surface mining industry, the Equipment Selection Problem involves choosing an appropriate fleet of trucks and loaders such that the long-term mine plan can be satisfied. An important characteristic for multi-location (multi-location and multi-dumpsite) mines is that the underlying problem is a multi-commodity flow problem. The problem is therefore at least as difficult as the fixed-charge, capacitated multi-commodity flow problem. For long-term schedules it is useful to consider both the purchase and salvage of the equipment, since equipment may be superseded, and there is the possibility of pre-existing equipment. This may also lead to heterogeneous fleets and arising compatibility considerations. In this paper, we consider two case studies provided by our industry partner. We develop a mixed-integer linear programming model for heterogeneous equipment selection in a surface mine with multiple locations and a multiple period schedule. Encoded in the solution is an allocation scheme in addition to a purchase and salvage policy. We develop a solution approach, including variable preprocessing, to tackle this large-scale problem. We illustrate the computational effectiveness of the resulting model on the two case studies for large sets of equipment and long-term schedule scenarios.

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تاریخ انتشار 2013