Multiple locations equipment selection
dc.contributor.author | Burt, C. | |
dc.contributor.author | Caccetta, Louis | |
dc.date.accessioned | 2018-05-18T08:01:23Z | |
dc.date.available | 2018-05-18T08:01:23Z | |
dc.date.created | 2018-05-18T00:23:06Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Burt, C. and Caccetta, L. 2018. Multiple locations equipment selection. In Studies in Systems, Decision and Control, 91-114. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/68235 | |
dc.identifier.doi | 10.1007/978-3-319-76255-5_7 | |
dc.description.abstract |
© 2018, Springer International Publishing AG. In this chapter we consider a multi-location mining operation. 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For long-term schedules it is useful to consider both the purchase and salvage of the equipment, since equipment may be superseded, and there is the possibility of used pre-existing equipment. This may also lead to heterogeneous fleets and arising compatibility considerations. In this chapter, we consider two case studies provided by our industry partner. We develop a large-scale 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. | |
dc.title | Multiple locations equipment selection | |
dc.type | Book Chapter | |
dcterms.source.volume | 150 | |
dcterms.source.startPage | 91 | |
dcterms.source.endPage | 114 | |
dcterms.source.title | Studies in Systems, Decision and Control | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |