The integrated optimization of underground stope layout designing and production scheduling incorporating a non-dominated sorting genetic algorithm (NSGA-II)

Sorayya Foroughi, Jafar Khademi Hamidi, Masoud Monjezi and Micah Nehring

Resources Policy, 2019, vol. 63, issue C, -

Abstract: Stope layout designing and production scheduling are main phases to determine the profitability of an underground mining project. These are mainly related to the output of one phase, which has a significant impact on generating of the next phase. Individual optimization of these two phases results only in a local optimal solution. To date, the integrated optimization of these phases has been carried out to maximize net present value (NPV). In this paper, a multi-objective integer programming model (MOIP) was developed to optimize this integrated problem in a sublevel stoping operation. The non-dominated sorting genetic algorithm (NSGA-II) was incorporated to solve the objective functions. The Pareto front generated by NSGA-II showed good convergence and diversity with the solution time decreasing significantly (from 7-8 days to 6–7 h). The most preferred solution point on the Pareto front increased recovery by 18.55% in exchange for a 0.41% reduction in NPV with respect to the single objective optimization to maximize NPV.

Keywords: Integrated optimization; Stope layout; Production scheduling; Multi-objective integer programming (MOIP); Non-dominated sorting genetic algorithm (NSGA-II); Sublevel stopping (SLS) (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:63:y:2019:i:c:49

DOI: 10.1016/j.resourpol.2019.101408

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