Production planning and scheduling in mining scenarios under IPCC mining systems

Samavati, M; Essam, D; Nehring, M; Sarker, R

Production planning and scheduling in mining scenarios under IPCC mining systems

Samavati, M

Essam, D Nehring, M Sarker, R

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Publisher:: PERGAMON-ELSEVIER SCIENCE LTD
Publication Type:: Journal Article
Citation:: Computers and Operations Research, 2020, 115
Issue Date:: 2020-03-01

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Field	Value	Language
dc.contributor.author	Samavati, M https://orcid.org/0000-0002-3468-9155
dc.contributor.author	Essam, D
dc.contributor.author	Nehring, M
dc.contributor.author	Sarker, R
dc.date.accessioned	2020-05-11T04:22:08Z
dc.date.available	2020-05-11T04:22:08Z
dc.date.issued	2020-03-01
dc.identifier.citation	Computers and Operations Research, 2020, 115
dc.identifier.issn	0305-0548
dc.identifier.issn	1873-765X
dc.identifier.uri	http://hdl.handle.net/10453/140622
dc.description.abstract	© 2019 Elsevier Ltd The open pit mine production scheduling problem (OPMPSP) consists of scheduling material extraction in a mineral deposit over a horizon of several time periods such that the profit of the operation is maximized and a variety of operational constraints are satisfied. These constraints vary depending on the extraction system used by the mining company for extracting material. Two extraction systems are available in the mining industry – Truck and Shovel (T&S) and In-pit Crusher Conveyor (IPCC). IPCC systems offer an alternative to conventional T&S systems by completely replacing trucks with conveyors. This replacement introduces a number of additional sequencing constraints that are not required in traditional T&S systems. These additional constraints add further complexity to an already complex large scale OPMPSP. While OPMPSP has been extensively studied and a number of optimization techniques have been successfully applied, it is very much unresolved when IPCC systems are used; in most cases, industry still relies on the judgement or best estimate of experienced personnel. In this paper, we develop a new integer programming model of OPMPSP-IPCC and present an algorithm to address practical sized instances. The performance of the developed algorithm is also evaluated.
dc.language	English
dc.publisher	PERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartof	Computers and Operations Research
dc.relation.isbasedon	10.1016/j.cor.2019.05.019
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0102 Applied Mathematics, 0103 Numerical and Computational Mathematics
dc.subject.classification	Operations Research
dc.title	Production planning and scheduling in mining scenarios under IPCC mining systems
dc.type	Journal Article
utslib.citation.volume	115
utslib.for	0102 Applied Mathematics
utslib.for	0103 Numerical and Computational Mathematics
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2020-05-11T04:22:06Z
pubs.publication-status	Published
pubs.volume	115

Abstract:

© 2019 Elsevier Ltd The open pit mine production scheduling problem (OPMPSP) consists of scheduling material extraction in a mineral deposit over a horizon of several time periods such that the profit of the operation is maximized and a variety of operational constraints are satisfied. These constraints vary depending on the extraction system used by the mining company for extracting material. Two extraction systems are available in the mining industry – Truck and Shovel (T&S) and In-pit Crusher Conveyor (IPCC). IPCC systems offer an alternative to conventional T&S systems by completely replacing trucks with conveyors. This replacement introduces a number of additional sequencing constraints that are not required in traditional T&S systems. These additional constraints add further complexity to an already complex large scale OPMPSP. While OPMPSP has been extensively studied and a number of optimization techniques have been successfully applied, it is very much unresolved when IPCC systems are used; in most cases, industry still relies on the judgement or best estimate of experienced personnel. In this paper, we develop a new integer programming model of OPMPSP-IPCC and present an algorithm to address practical sized instances. The performance of the developed algorithm is also evaluated.

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http://hdl.handle.net/10453/140622