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dc.contributor.authorBurt, C.
dc.contributor.authorCaccetta, Louis
dc.date.accessioned2018-05-18T07:59:41Z
dc.date.available2018-05-18T07:59:41Z
dc.date.created2018-05-18T00:23:06Z
dc.date.issued2018
dc.identifier.citationBurt, C. and Caccetta, L. 2018. Single location equipment selection. In Studies in Systems, Decision and Control, 75-90.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/67779
dc.identifier.doi10.1007/978-3-319-76255-5_6
dc.description.abstract

© 2018, Springer International Publishing AG. In a simple surface mining scenario we can consider the mine to have one mining location and one dump-site connected by a single truck route. Our objective is to determine a purchase and salvage policy for trucks and loaders such that the cost of materials handling is minimized over a multiple period schedule. This problem quickly becomes large scale when we consider large sets of possible trucks and loaders, and long schedules. The inclusion of pre-existing equipment leads to the possibility of heterogeneous fleets, and the non-uniform behaviour of different equipment types (with respect to operating cost, availability and productivity) coupled with compatibility issues adds to the complexity of the problem. In this chapter, we present an integer linear program model for equipment selection that incorporates heterogeneous fleets and pre-existing equipment while optimising over multiple periods. We introduce a specialized linear constraint set to ensure satisfaction of production requirements while accounting for equipment compatibility. We also test the model on a truck and loader case study for surface mines. The resulting model is a robust equipment selection tool that obtains optimal solutions quickly for large sets of equipment and long schedules. Many aspects of the presented model, such as the consideration of multiple periods and pre-existing equipment, are novel for the mining industry and ensure that the model is both a new and advanced equipment selection tool.

dc.titleSingle location equipment selection
dc.typeBook Chapter
dcterms.source.volume150
dcterms.source.startPage75
dcterms.source.endPage90
dcterms.source.titleStudies in Systems, Decision and Control
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusFulltext not available


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