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Conference Proceedings

35th APCOM Symposium 2011

Conference Proceedings

35th APCOM Symposium 2011

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Integration of Oil Sands Mine Planning and Waste Management Using Goal Programmin

Mine planning is the backbone of all mining enterprises and determines the profitability or otherwise of any mining investment. Providing high quality ore and tailings containment at the right time are the main drivers in oil sands mining. Recent environmental and regulatory requirements also makes waste management an integral part of mine planning in the oil sands industry (Directive 074). Due to the limitation of lease area, the pit phase advancement in oil sands mining is carried out simultaneously with the construction of tailings dykes in the mined out areas of the pit. These in-pit dykes are constructed to hold tailings that are produced during the processing of the oil sands ore after an initial external tailings facility. Most of the materials used in constructing these in-pit and ex-pit dykes come from the oil sands mining operation, making it necessary to have a plan for supplying the dyke material. The research problem here is categorised as: determining the order of extraction of ore, dyke material and waste to be removed from a predefined ultimate pit limit over the mine life that maximises the net present value of the operation - a strategic schedule; anddetermining the destination of dyke material that minimises construction cost depending on the construction requirements of the various dykes as per their designs - an operational schedule. There has been developed, implemented and verified a theoretical optimisation framework based on mixed integer goal programming (MIGP) to address the oil sands long-term production scheduling and waste management problem. The research introduced the development of multiple material types and multiple destination optimisation techniques using MIGP in the context of mine planning. This study presents an integration of mixed integer programming and goal programming in solving large-scale mine planning optimisation problems using clustering and pushback techniques.
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  • Published: 2010
  • PDF Size: 0.476 Mb.
  • Unique ID: P201111030

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