Using aggregation to optimize long-term production planning at an underground mine [An article from: European Journal of Operational Research] | ![Using aggregation to optimize long-term production planning at an underground mine [An article from: European Journal of Operational Research]](http://ecx.images-amazon.com/images/I/51G4P0G7AGL._SL160_.jpg)
 enlarge | Authors: A.m. Newman, M. Kuchta
Publisher: Elsevier
Category: Book
Buy New: $7.95
Format: Html
Media: Digital
Publication Date: January 16, 2007
Availability: Available for download now
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Product Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Motivated by an underground mining operation at Kiruna, Sweden, we formulate a mixed integer program to schedule iron ore production over multiple time periods. Our optimization model determines an operationally feasible ore extraction sequence that minimizes deviations from planned production quantities. The number of binary decision variables in our model is large enough that directly solving the full, detailed problem for a three year time horizon requires hours, or even days. We therefore design a heuristic based on solving a smaller, more tractable, model in which we aggregate time periods, and then solving the original model using information gained from the aggregated model. We compute a bound on the worst case performance of this heuristic and demonstrate empirically that this procedure produces good quality solutions while substantially reducing computation time for problem instances from the Kiruna mine.
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