Medium-Term Rail Scheduling for an Iron Ore Mining Company

Gaurav Singh (), Rodolfo García-Flores (), Andreas Ernst (), Palitha Welgama (), Meimei Zhang () and Kerry Munday ()
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Gaurav Singh: CSIRO Mathematics, Informatics and Statistics, Clayton, Victoria 3168, Australia
Rodolfo García-Flores: CSIRO Mathematics, Informatics and Statistics, Clayton, Victoria 3168, Australia
Andreas Ernst: CSIRO Mathematics, Informatics and Statistics, Clayton, Victoria 3168, Australia
Palitha Welgama: Rio Tinto Iron Ore, Operations Center, Perth Domestic Airport, Western Australia 6105, Australia
Meimei Zhang: Rio Tinto Iron Ore, Operations Center, Perth Domestic Airport, Western Australia 6105, Australia
Kerry Munday: Rio Tinto Iron Ore, Operations Center, Perth Domestic Airport, Western Australia 6105, Australia

Interfaces, 2014, vol. 44, issue 2, 222-240

Abstract: In mineral supply chains, medium-term plans are made for scheduling crews, production, and maintenance. These plans must respect constraints associated with loading and unloading, stockyard capacities, fleet capacities, and maintenance and production requirements. Additionally, compliance with grade quality depends on blending minerals from different sources. In this paper, we present an optimization tool developed for a major multinational iron ore mining company to manage the operations of its supply network in the Pilbara region of Western Australia. The tool produces plans for time horizons from a few weeks to two years, while addressing the nonlinearities that blending introduces. The plans our tool produces allow the company to ship a higher amount of iron ore than it did when it followed the plans obtained by its former manual approach. The company’s planners now rely solely on our tool because it has enabled them to schedule up to one million additional tonnes of material per annum and has reduced the planning time from five hours to less than one hour.

Keywords: scheduling; rail planning; medium-term planning; blending; mixed-integer nonlinear programming (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (4)

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