A Novel Approach to Integrating Uncertainty into a Push Re-Label Network Flow Algorithm for Pit Optimization

Devendra Joshi, Marwan Ali Albahar, Premkumar Chithaluru (), Aman Singh, Arvind Yadav and Yini Miro
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Devendra Joshi: Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur 522002, India
Marwan Ali Albahar: Department of Computer Science, Umm Al Qura University, Mecca 24382, Saudi Arabia
Premkumar Chithaluru: Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India
Aman Singh: Higher Polytechnic School, Universidad Europea del Atlántico, C/Isabel Torres 21, 39011 Santander, Spain
Arvind Yadav: Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur 522002, India
Yini Miro: Higher Polytechnic School, Universidad Europea del Atlántico, C/Isabel Torres 21, 39011 Santander, Spain

Mathematics, 2022, vol. 10, issue 24, 1-20

Abstract: The standard optimization of open-pit mine design and production scheduling, which is impacted by a variety of factors, is an essential part of mining activities. The metal uncertainty, which is connected to supply uncertainty, is a crucial component in optimization. To address uncertainties regarding the economic value of mining blocks and the general problem of mine design optimization, a minimum-cut network flow algorithm is employed to give the optimal ultimate pit limits and pushback designs under uncertainty. A structure that is computationally effective and can manage the joint presentation and treatment of the economic values of mining blocks under various circumstances is created by the push re-label minimum-cut technique. In this study, the algorithm is put to the test using a copper deposit and shows similarities to other stochastic optimizers for mine planning that have already been created. Higher possibilities of reaching predicted production targets are created by the algorithm’s earlier selection of more certain blocks with blocks of high value. Results show that, in comparison to a conventional approach using the same algorithm, the cumulative metal output is larger when the uncertainty in the metal content is taken into consideration. There is also an additional 10% gain in net present value.

Keywords: open-pit mine; ultimate pit limit; uncertainty modeling; minimum cut; network flow (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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