A stochastic particle swarm based model for long term production planning of open pit mines considering the geological uncertainty

Long term production planning (LTPP) plays a critical role to achieve success of a mining operation. LTPP, as an optimization problem, aims to maximize the net present value (NPV) of a mine subject to a set of constraints. One of the main reasons for not achieving production targets is the uncertain...

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Bibliographic Details
Published in:Resources policy Vol. 68; p. 101738
Main Authors: Gilani, Seyyed-Omid, Sattarvand, Javad, Hajihassani, Mohsen, Abdullah, Shahrum Shah
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.10.2020
Elsevier Science Ltd
Subjects:
Algorithms
Copper
Function words
Geological uncertainty
Geology
Integer programming
Long term
Long term production planning
Mining
Net present value
Open pit mining
Optimization
Present value
Production
Production planning
PSO
Risk
Schedules
Strategies
Swarm intelligence
Topology
Uncertainty
Open pit mining
Long term production planning
Copper
Geological uncertainty
PSO
ISSN:0301-4207, 1873-7641
Online Access:Get full text
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Summary:Long term production planning (LTPP) plays a critical role to achieve success of a mining operation. LTPP, as an optimization problem, aims to maximize the net present value (NPV) of a mine subject to a set of constraints. One of the main reasons for not achieving production targets is the uncertainty of the LTPP's inputs. Geological uncertainty as the main sources of uncertainty is considered in this research. In this regard, a set of equiprobable scenarios of orebody and derived two new block model called “risk block model” and “EType” were used as inputs. Then, a stochastic integer programming (SIP) model was developed to integrate the geological uncertainty. Finally, a PSO-based algorithm was developed to solve the SIP model. Four different strategies were developed, according to the population topology and how to use the risk block model. Population topology defines the subset of particles that effect on each particle. Implementation the proposed approach on a large scale mine demonstrate its performance to develop a unique schedule considering geological uncertainties with maximum NPV and minimum risk of not achieving production targets. Investigations show that Gbest based PSO is more susceptible to trap in local optima. Multiple risk based strategies are able to generate better solutions, however, single risk based strategies are good practices when companies are looking for flexible or specific risk based designs. •A new stochastic optimization algorithm based on PSO is proposed for open pit mine production planning.•Geological uncertainty is considered.•Four different strategies named GPSO-SRB, GPSO-MRB, LPSO-SRB, and LPSO-MRB were developed.•The approach was applied on large scale open pit mine in the northwest of Iran.•Results demonstrate the abilities of approach to create a single schedule that diminishes the risk and also increases the NPV.
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ISSN:0301-4207
1873-7641
DOI:10.1016/j.resourpol.2020.101738