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Improving performance of open-pit mine production scheduling problem under grade uncertainty by hybrid algorithms

Journal of Central South University 2020年第9期27卷 2479-2493页

作者： Kamyar TOLOUEI Ehsan MOOSAVI Amir Hossein BANGIAN TABRIZI Peyman AFZAL abbas aghajani bazzazi Department of Petroleum and Mining Engineering South Tehran BranchIslamic Azad UniversityTehranIran Department of Mining Engineering University of KashanKashanIran

One of the surface mining methods is open-pit mining,by which a pit is dug to extract ore or waste downwards from the earth’s *** the mining industry,one of the most significant difficulties is long-term production scheduling(LTPS)of the open-pit *** and uncertainty-based approaches are identified as the main strategies,which have been widely used to cope with this *** the last few years,many researchers have highly considered a new computational type,which is less costly,i.e.,meta-heuristic methods,so as to solve the mine design and production scheduling *** the optimality of the final solution cannot be guaranteed,they are able to produce sufficiently good solutions with relatively less computational *** the present paper,two hybrid models between augmented Lagrangian relaxation(ALR)and a particle swarm optimization(PSO)and ALR and bat algorithm(BA)are suggested so that the LTPS problem is solved under the condition of grade *** is suggested to carry out the ALR method on the LTPS problem to improve its performance and accelerate the ***,the Lagrangian coefficients are updated by using PSO and *** presented models have been compared with the outcomes of the ALR-genetic algorithm,the ALR-traditional sub-gradient method,and the conventional method without using the Lagrangian *** results indicated that the ALR is considered a more efficient approach which can solve a large-scale problem and make a valid ***,it is more effectual than the conventional ***,the time and cost of computation are diminished by the proposed hybrid *** CPU time using the ALR-BA method is about 7.4%higher than the ALR-PSO approach.

关键词： open-pit mine long-term production scheduling grade uncertainty augmented Lagrangian relaxation particle swarm optimization algorithm bat algorithm

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Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment

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International Journal of Mining Science and Technology 2016年第6期26卷 1017-1023页

作者： Alizadeh Shahab Salari Rad Mohammad Mehdi bazzazi abbas aghajani Mining Engineering Department Amirkabir University of Technology Tehran *** Iran Mining Engineering Department University of Kashan Kashan *** Iran

Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of *** this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.

关键词： Alunite Mineral processing methods Multi Attribute Decision Making Delphi Analytical Hierarchy Process (DAHP)Fuzzy TOPSIS

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