Preprint Article Version 2 This version is not peer-reviewed

Production Process Optimization of Metal Mines Considering Economic Benefit and Resource Efficiency Using an NSGA-II Model

Version 1 : Received: 29 June 2018 / Approved: 3 July 2018 / Online: 3 July 2018 (10:23:12 CEST)
Version 2 : Received: 27 November 2018 / Approved: 29 November 2018 / Online: 29 November 2018 (10:59:56 CET)

A peer-reviewed article of this Preprint also exists.

Wang, X.; Gu, X.; Liu, Z.; Wang, Q.; Xu, X.; Zheng, M. Production Process Optimization of Metal Mines Considering Economic Benefit and Resource Efficiency Using an NSGA-II Model. Processes 2018, 6, 228. Wang, X.; Gu, X.; Liu, Z.; Wang, Q.; Xu, X.; Zheng, M. Production Process Optimization of Metal Mines Considering Economic Benefit and Resource Efficiency Using an NSGA-II Model. Processes 2018, 6, 228.

Journal reference: Processes 2018, 6, 228
DOI: 10.3390/pr6110228

Abstract

The optimization of the production process of metal mines has been traditionally driven only by economic benefits while ignoring resource efficiency. However, it has become increasingly aware of the importance of resource efficiency since mineral resource reserves continue to decrease while the demand continues to grow. To better utilize the mineral resources for sustainable development, this paper proposes a multi-objective optimization model of the production process of metal mines considering both economic benefits and resource efficiency. Specifically, the goals of the proposed model are to maximize the profit and resource utilization rate. Then, the fast and elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize the multi-objective optimization model. The proposed model has been applied to the optimization of the production process of a stage in the Huogeqi Copper Mine. The optimization results provide a set of Pareto-optimal solutions that can meet varying needs of decision makers. Moreover, compared with those of the current production indicators, the profit and resource utilization rate of some points in the optimization results can increase respectively by 2.99% and 2.64%. Additionally, the effects of the decision variables (geological cut-off grade, minimum industrial grade and loss ratio) on objective functions (profit and resource utilization rate) were discussed using variance analysis. The sensitivities of the Pareto-optimal solutions to the unit copper concentrate price were studied. The results show that the Pareto-optimal solutions at higher profits (with lower resource utilization rates) are more sensitive to the unit copper concentrate prices than those obtained in regions with lower profits.

Subject Areas

multi-objective optimization; resource efficiency; metal mines; production process; NSGA-II

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