عنوان مقاله [English]
نویسندگان [English]چکیده [English]
In flotation, it is customary to use more than one stage to achieve an acceptable level of separation of valuable minerals. Flotation circuit design is usually accomplished using empirical rules which at most cases they do not operate at optimum conditions. In design and optimization of flotation circuits, genetic algorithms could be used. In flotation circuit configuration optimization problem, metallurgical parameters such as yield and ash content could be used as the fitness function for the algorithm. Since there is a tradeoff between the yield and concentrate ash content (i.e., they move in opposite directions), multi-objective optimization methods are needed. Optimization of the Zarand coal processing plant flotation circuit was carried out by two methods: sum of weighted factors and Pareto optimum. The results indicated that it is possible to increase the yield from 57.6% for the current configuration to 65.8% for the proposed one. This was achieved by a three-stage configuration while keeping the quality of the concentrate ash content (10.9%) within an acceptable level.