Two-stage clustering algorithm for block aggregation in open pit mines

One of the main obstacles in using exact optimisation methods for open pit production scheduling is the size of real mining problems, which forms an intractable optimisation problem. The objective of this paper is to develop, implement, verify and validate a clustering algorithm for block aggregation for the purpose of production scheduling. The algorithm aggregates blocks into selective mining units based on a similarity index which is defined based on rock types, ore grades and distances between blocks. A two-stage clustering approach based on agglomerative hierarchical algorithm and tabu search is developed and tested. The algorithm is validated by a case study on an iron ore life of mine production schedule. The results illustrate that the size and shape of the aggregated blocks have 10–15% effect on the project's net present value and also a significant impact on the practicality of long term production schedules genereated.