Flotation Column Performance Optimisation based on Imperialist Competitive Algorithm

Abstract

Optimisation in flotation columns is an important factor that influences the recovery and the grade of concentrate from the column. A column flotation process is a nonlinear, multi-variable problem with changeable parameters that traditional methods have difficulty optimising. Finding the optimum values of the column flotation variables is difficult due to the presence of many variables, large size of the search space, and many constraints. In this study, a novel optimisation method is presented based on a socio-politically motivated strategy, called imperialist competitive algorithm (ICA) which is paired with the multivariate non-linear regression (MNLR) model of the column flotation metallurgical performance as fitness function to optimise the operation parameters of flotation column in order to produce the optimum grade and recovery with respect to control parameter. The designed ICA system uses the practical data of pilot plant located in Sarcheshmeh copper complex. The results indicate that the proposed ICA finds accurately the best values of flotation column model parameters with error 1.36 x 10-16.

Department(s)

Mining Engineering

Keywords and Phrases

Flotation column; Grade; ICA; Imperialist competitive algorithm; Recovery; Simultaneous optimisation

International Standard Serial Number (ISSN)

1754-8918; 1754-890X

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2024 Inderscience, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

07 Feb 2016

Link to Full Text

Share

 
COinS