Case studies
dc.contributor.author | Burt, C. | |
dc.contributor.author | Caccetta, Louis | |
dc.date.accessioned | 2018-05-18T07:58:57Z | |
dc.date.available | 2018-05-18T07:58:57Z | |
dc.date.created | 2018-05-18T00:23:06Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Burt, C. and Caccetta, L. 2018. Case studies. In Studies in Systems, Decision and Control, 65-74. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/67558 | |
dc.identifier.doi | 10.1007/978-3-319-76255-5_5 | |
dc.description.abstract |
© 2018, Springer International Publishing AG. Our aim is to develop effective computational models for determining the optimal truck-loader selection and allocation strategy for use in large and complex mining operations. To achieve this it is important to have real case studies that reflect the true nature of the problems to be addressed. In this chapter, we provide the data and background for two real case studies, one is a simple senario with one mining location and 9 periods each having a 1-year duration, the other is a more complex senario with multiple locations and 13 periods each having a 1-year duration. Our first case study, though small and simple has interesting variation in truck cycle times. It represents a mine in the planning stage with pre-existing equipment. Our second case study, is from an ongoing mining operation and has pre-existing equipment and includes stockpiles. This data was provided by an in-house equipment selection expert from an industry partner. | |
dc.title | Case studies | |
dc.type | Book Chapter | |
dcterms.source.volume | 150 | |
dcterms.source.startPage | 65 | |
dcterms.source.endPage | 74 | |
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 |
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