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Optimization of comminution circuit simulations based on genetic algorithms search method / A. Farzanegan in Minerals engineering, Vol. 22 N° 7/8 (Juin/Juillet 2009) 

Public ISBD [article]  in Minerals engineering > Vol. 22 N° 7/8 (Juin/Juillet 2009) . - pp. 719–726 Titre : Optimization of comminution circuit simulations based on genetic algorithms search method Type de document : texte imprimé Auteurs : A. Farzanegan, Auteur ; S.M. Vahidipour, Auteur Année de publication : 2009 Article en page(s) : pp. 719–726 Note générale : Génie Minier Langues : Anglais (eng) Mots-clés : Comminution  Modeling  Simulation  Evolutionary  optimization  Genetic  algorithms Résumé : Comminution simulators are extensively used by mineral processing engineers for plant design and optimization purposes. Recently, there had been a great progress in developing new and more powerful optimization methods such as Genetic Algorithms (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Tabu Search Algorithm (TSA). Simulation optimization is required if one wants to find the best steady-state values of important process variables. In this paper, the authors investigated the integration of GA optimization algorithm with a pre-existing grinding circuit simulator called Ball Milling Circuits Simulator (BMCS) in MATLAB™ environment. The BMCS code has been written in ANSI C language and has been validated against real industrial grinding circuit data sets. Various C modules of the BMCS grinding software were restructured under a new single source code file so that it can be imported into MATLAB. Then, a number of input simulation data were identified and selected as possible process variables (e.g., solids flow rate, water addition rate, and number of operating cyclones) which must be optimized in order to achieve a pre-defined process objective (e.g., a specific d80 of circuit output). The obtained results show that BMCS simulation trials can be successfully optimized by applying evolutionary algorithms via MATLAB toolboxes. This allows the mineral processor to perform automatic repetitive simulations to find the possible solutions of the problem at hand quickly. DEWEY : 622 ISSN : 0892-6875 En ligne : http://www.sciencedirect.com/science/article/pii/S0892687509000533 [article] Optimization of comminution circuit simulations based on genetic algorithms search method [texte imprimé] / A. Farzanegan, Auteur ; S.M. Vahidipour, Auteur . - 2009 . - pp. 719–726. Génie Minier Langues : Anglais (eng) in Minerals engineering > Vol. 22 N° 7/8 (Juin/Juillet 2009) . - pp. 719–726 Mots-clés : Comminution  Modeling  Simulation  Evolutionary  optimization  Genetic  algorithms Résumé : Comminution simulators are extensively used by mineral processing engineers for plant design and optimization purposes. Recently, there had been a great progress in developing new and more powerful optimization methods such as Genetic Algorithms (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and Tabu Search Algorithm (TSA). Simulation optimization is required if one wants to find the best steady-state values of important process variables. In this paper, the authors investigated the integration of GA optimization algorithm with a pre-existing grinding circuit simulator called Ball Milling Circuits Simulator (BMCS) in MATLAB™ environment. The BMCS code has been written in ANSI C language and has been validated against real industrial grinding circuit data sets. Various C modules of the BMCS grinding software were restructured under a new single source code file so that it can be imported into MATLAB. Then, a number of input simulation data were identified and selected as possible process variables (e.g., solids flow rate, water addition rate, and number of operating cyclones) which must be optimized in order to achieve a pre-defined process objective (e.g., a specific d80 of circuit output). The obtained results show that BMCS simulation trials can be successfully optimized by applying evolutionary algorithms via MATLAB toolboxes. This allows the mineral processor to perform automatic repetitive simulations to find the possible solutions of the problem at hand quickly. DEWEY : 622 ISSN : 0892-6875 En ligne : http://www.sciencedirect.com/science/article/pii/S0892687509000533