New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

Liu, Shi Qiang & Kozan, Erhan (2016) New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems. Expert Systems With Applications, 43, pp. 59-65.

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Abstract

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

Impact and interest:

5 citations in Scopus
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8 citations in Web of Science®

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ID Code: 87292
Item Type: Journal Article
Refereed: Yes
Keywords: Mine optimisation algorithms, planning and scheduling, mine block sequencing, ultimate pit limit, constrained pit limit, network flow graph
DOI: 10.1016/j.eswa.2015.08.044
ISSN: 1873-6793
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > APPLIED MATHEMATICS (010200) > Operations Research (010206)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > RESOURCES ENGINEERING AND EXTRACTIVE METALLURGY (091400) > Mining Engineering (091405)
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
  • CRC ORE/P3B-023_Q22013
Deposited On: 07 Sep 2015 05:35
Last Modified: 14 Dec 2015 06:00

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