Simultaneous optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm - II. More complex problems

Guria, Chandan ; Varma, Mohan ; Mehrotra, Surya P. ; Gupta, Santosh K. (2006) Simultaneous optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm - II. More complex problems International Journal of Mineral Processing, 79 (3). pp. 149-166. ISSN 0301-7516

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Official URL: http://www.sciencedirect.com/science/article/pii/S...

Related URL: http://dx.doi.org/10.1016/j.minpro.2006.01.008

Abstract

The binary-coded elitist non-dominated sorting genetic algorithm with the modified jumping gene operator (NSGA-II-mJG) is used to obtain global optimal solutions of flotation circuits. Several single-objective and multi-objective optimization problems are solved using the interconnecting cell linkage parameters (fraction flow rates) and the mean cell residence times as the decision variables. In the single-objective problem, the overall recovery of the concentrate stream is maximized for a desired grade of the concentrate. Two two-objective optimization problems are then solved. In one, the number of non-linking streams and the overall recovery of the concentrate are maximized simultaneously. This gives several simple circuits in a systematic manner with only marginally lower recoveries. In the other two-objective optimization problem, the overall recovery of the concentrate is maximized while the total cell volume is minimized. A three-objective problem (maximization of the overall recovery of the concentrate, maximization of the number of non-linking streams and minimization of the total cell volume) is then solved. All the problems constrain the grade of the product to lie at a fixed value. Finally, a complex and computationally intensive four-objective optimization problem is solved. The solution of several practical optimization problems in this study helps develop useful insights into the optimal solutions.

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Froth Flotation; Mineral Processing; Circuit; Network Optimization; Global Optimal; Jumping Gene; Genetic Algorithm; Multi-objective Optimization
ID Code:76470
Deposited On:31 Dec 2011 14:30
Last Modified:31 Dec 2011 14:30

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