Determination of the optimum cut-off grades and production scheduling in multi-product open pit mines using imperialist competitive algorithm (ICA). (March 2017)

• Record Type: Journal Article
• Authors: Mohammadi, Sadjad; Kakaie, Reza; Ataei, Mohammad; Pourzamani, Eshagh
• Is Part Of: Resources policy. Volume 51(2017)
• Page Start: 39
• Page End: 48
• Publication Date: 2017-03
• Subjects: Open pit mines -- Optimum cut-off grade -- Production scheduling -- Meta-heuristic algorithm -- ICA -- Golgohar iron mine; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Ressources naturelles -- Gestion -- Périodiques; Environnement -- Politique gouvernementale -- Périodiques; 333.8
• DOI: 10.1016/j.resourpol.2016.11.005
• Languages: English
• ISSNs: 0301-4207

Abstract

Abstract: With regard to the immense importance of cut-off grade in designing and planning open pit mines, optimizing this parameter has considerable effects in mining economic. This paper describes objective function for single metal mines with multi-product. For this purpose, the operation process in mine No.1 of the Golgohar iron mine that produces three types of products (sizing, concentrate and pellet) for sales is used to model objective function. Then the Imperialist Competitive Algorithm (ICA) has been utilized to find out the optimum cut-off grades. Consequently, the optimum cut-off grades has been calculated between 40.5 and 47.5% and net present value has been obtained 18, 142 billion Rial. In addition, production scheduling is carried out for five years mining plan pushback. Therefore, the average stripping ratio has been determined 1.41. The result shows that by stockpiling low-grade ore, concentrate plant can be fed by maximum capacity for one year addition to the primary plan. Highlights: Developing a new model to determining the optimum cut-off grades (OCOG) for single metal open pit mines with multi-product. Determining the production scheduling based on the optimum cut-off grades strategy. Use of Imperialist Competitive Algorithm to solve the optimization problem.