Name
Abstract | ||
|---|---|---|
AbstractIn 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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1287/inte.1120.0669 | Periodicals |
Keywords | Field | DocType |
scheduling, rail planning, medium-term planning, blending, mixed-integer nonlinear programming | Supply network,Multinational corporation,Scheduling (computing),Supply chain,Engineering,Operations management,Iron ore | Journal |
Volume | Issue | ISSN |
44 | 2 | 0092-2102 |
Citations | PageRank | References |
4 | 0.42 | 12 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gaurav Singh | 1 | 55 | 7.54 |
| Rodolfo García-Flores | 2 | 42 | 5.28 |
| Andreas T. Ernst | 3 | 1198 | 82.51 |
| P Welgama | 4 | 28 | 2.18 |
| Meimei Zhang | 5 | 4 | 0.42 |
| Kerry Munday | 6 | 4 | 0.42 |