Medium-Term Rail Scheduling for an Iron Ore Mining Company

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.

[1]  James R. Evans,et al.  Heuristic “Optimization”: Why, When, and How to Use It , 1981 .

[2]  Eric R. Zieyel.  Operations research : applications and algorithms , 1988 .

[3]  L. Shih.  Planning of fuel coal imports using a mixed integer programming method , 1997 .

[4]  Paolo Toth,et al.  A Survey of Optimization Models for Train Routing and Scheduling , 1998, Transp. Sci..

[5]  H. Sherali,et al.  A coal shipping and blending problem for an electric utility company , 2000 .

[6]  Candace Arai Yano,et al.  Centralized and decentralized train scheduling for intermodal operations , 2000 .

[7]  Jim E. Everett,et al.  Iron ore production scheduling to improve product quality , 2001, Eur. J. Oper. Res..

[8]  Pierre Hansen,et al.  Pooling Problem: Alternate Formulations and Solution Methods , 2000, Manag. Sci..

[9]  Cathy Macharis,et al.  Opportunities for OR in intermodal freight transport research: A review , 2004, Eur. J. Oper. Res..

[10]  Fred W. Glover,et al.  The feasibility pump , 2005, Math. Program..

[11]  Ignacio E. Grossmann,et al.  A simultaneous optimization approach for off-line blending and scheduling of oil-refinery operations , 2006, Comput. Chem. Eng..

[12]  Jim Everett,et al.  Computer aids for production systems management in iron ore mining , 2007 .

[13]  Nina Linn Ulstein,et al.  Tactical planning of offshore petroleum production , 2007, Eur. J. Oper. Res..

[14]  Bilge Bilgen,et al.  A mixed-integer linear programming model for bulk grain blending and shipping , 2007 .

[15]  Gerrit K. Janssens,et al.  Planning Problems in Intermodal Freight Transport: Accomplishments and Prospects , 2008 .

[16]  Otto Rentz,et al.  Integrated planning of transportation and recycling for multiple plants based on process simulation , 2010, Eur. J. Oper. Res..

[17]  Elise Miller-Hooks,et al.  Freight train scheduling with elastic demand , 2010 .

[18]  Tom Sandeman,et al.  Integrating optimization and simulation - A comparison of two case studies in mine planning , 2010, Proceedings of the 2010 Winter Simulation Conference.

[19]  Mohammad Waqar Ali Asad,et al.  A Mixed-Integer Linear Programming (MILP) Model for Short-Range Production Scheduling of Cement Quarry Operations , 2010, Asia Pac. J. Oper. Res..

[20]  Andreas T. Ernst,et al.  Medium-term rail planning at Rio Tinto Iron Ore , 2011 .

[21]  Alexandra M. Newman,et al.  A sliding time window heuristic for open pit mine block sequencing , 2011, Optim. Lett..

[22]  M. Kumral,et al.  Incorporating geo-metallurgical information into mine production scheduling , 2011, J. Oper. Res. Soc..