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thesis for the degree of licentiate of engineering simulation and optimisation of crushing plant performance per svedensten department of machine and vehicle systems chalmers university of technology gÖteborg, sweden may 2004

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Each individual is represented by a DNA-string where each chromosome represents one optimisation variable of the crushing plant model. Use of a genetic evolutionary algorithm alone has been shown to be rather slow and not totally accurate for identifying the global optimum (Jaszkiewicz, 2002).

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[5] Per Svedensten, C. Magnus Evertsson, Crushing plant optimization by means of a genetic evolutionary algorithm; Minerals Engineering; 2005 [6] Kwade, A., Mill selection and process optimization using a physical grinding model, International journal of mineral processing, 2004

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characterization, modeling, optimization, evaluation, and implementation In this thesis, the complex compressive breakage behaviors of four different rock materials (i.e. gneiss, diabase, marble, and quartzite) and two different iron ores were experimentally studied and mathematically modeled. A genetic algorithm was also applied to theoretically

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Svedensten This approach of plant optimization is well suited to et al. (2005) developed a model for crushing plant satisfy single product quality constraint; however, the optimization by means of a genetic evolutionary procedure may become increasingly complex and algorithm.

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Apr 01, 2005· Crushing plant optimisation by means of a genetic evolutionary algorithm Crushing plant optimisation by means of a genetic evolutionary algorithm Svedensten, Per; Evertsson, C. Magnus 2005-04-01 00:00:00 Crushing plants are used both by aggregate producers and the mining industry. The overall crushed rock product production process can be improved by means of computer simulation and optimisation.

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Crushing plant optimisation by means of a genetic evolutionary algorithm. Per Svedensten, Magnus Evertsson. Minerals Engineering. Vol. 18 (5), p. 473-479 . Artikel i vetenskaplig tidskrift ... Simulation and optimisation of crushing plant performance. Per Svedensten. Licentiatavhandling

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Economic Optimisation of an Ore Processing Plant with a Constrained Multi-objective Evolutionary Algorithm. Authors; ... optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm. ... P., Evertsson, C.M.: Crushing plant optimisation by means of genetic evolutionary ...

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