Pareto based optimization of flotation cells configuration using an oriented genetic algorithm

Pirouzan, D.; Yahyaei, Mohsen; Banisi, S.

doi:10.1016/j.minpro.2013.12.001

Cited by 20 publications

(12 citation statements)

References 32 publications

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“…The objective is to obtain kinetic models based on the experimental data. For example, the experimental data for each laboratory condition can be adjusted using a fastslow flotation model (Pirouzan et al, 2014) to represent the behavior of particles with different levels of liberation.…”

Section: Step One: Experimental Kineticsmentioning

confidence: 99%

“…Examples of these procedures are the works of Schena et al (1997), Cisternas et al (2004Cisternas et al ( , 2006Cisternas et al ( , 2014, Méndez et al (2009), Hu et al (2013), and Pirouzan et al (2014). These procedures are difficult to solve; thus, in the literature, most authors use first-order models for banks (not cells) and consider few species.…”

Section: Introductionmentioning

confidence: 99%

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A strategy for the identification of optimal flotation circuits

Calisaya

López–Valdivieso

Cruz

et al. 2016

Minerals Engineering

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Section: Step One: Experimental Kineticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A strategy for the identification of optimal flotation circuits

Calisaya

López–Valdivieso

Cruz

et al. 2016

Minerals Engineering

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“…According to Pirouzan et al (2014) flotation circuit design can usually be accomplished by applying empirical rules, or by using the expertise of practitioners, which may result however in less-than-optimal operations of the plant. Keeping in mind the capabilities of genetic algorithms …”

Section: Application Of Genetic Algorithms In Flotation Processes Modmentioning

confidence: 99%

“…In recent studies, Pirouzan et al (2014) also applied a genetic algorithm, adjusted to the process rules, in an attempt to optimize the three-stage flotation circuit in a coal washing plant in Zarand (Kerman in Iran). A set of Pareto optimal solutions had thus been obtained -as the result of multi-objective optimization -from which, the authors chose the best solution.…”

Section: Goal Function Limitationsmentioning

confidence: 99%

Soft computing-based modeling of flotation processes – A review

Jovanović

Miljanović

Jovanović

2015

Minerals Engineering

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“…Similar to exact methods, the probability of finding the global solution using approximate methods decreases as the problem size increases [5]. In this context, according to Acosta-Flores et al [34] and Cisternas et al [2], the genetic algorithms are the only metaheuristic algorithms that have been used for designing flotation circuits [1,[35][36][37][38]. However, GA has been used only for small problems because its convergence is slow.…”

Section: Introductionmentioning

confidence: 99%

Design of Flotation Circuits Using Tabu-Search Algorithms: Multispecies, Equipment Design, and Profitability Parameters

2019

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The design of a flotation circuit based on optimization techniques requires a superstructure for representing a set of alternatives, a mathematical model for modeling the alternatives, and an optimization technique for solving the problem. The optimization techniques are classified into exact and approximate methods. The first has been widely used. However, the probability of finding an optimal solution decreases when the problem size increases. Genetic algorithms have been the approximate method used for designing flotation circuits when the studied problems were small. The Tabu-search algorithm (TSA) is an approximate method used for solving combinatorial optimization problems. This algorithm is an adaptive procedure that has the ability to employ many other methods. The TSA uses short-term memory to prevent the algorithm from being trapped in cycles. The TSA has many practical advantages but has not been used for designing flotation circuits. We propose using the TSA for solving the flotation circuit design problem. The TSA implemented in this work applies diversification and intensification strategies: diversification is used for exploring new regions, and intensification for exploring regions close to a good solution. Four cases were analyzed to demonstrate the applicability of the algorithm: different objective function, different mathematical models, and a benchmarking between TSA and Baron solver. The results indicate that the developed algorithm presents the ability to converge to a solution optimal or near optimal for a complex combination of requirements and constraints, whereas other methods do not. TSA and the Baron solver provide similar designs, but TSA is faster. We conclude that the developed TSA could be useful in the design of full-scale concentration circuits.

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Pareto based optimization of flotation cells configuration using an oriented genetic algorithm

Cited by 20 publications

References 32 publications

A strategy for the identification of optimal flotation circuits

A strategy for the identification of optimal flotation circuits

Soft computing-based modeling of flotation processes – A review

Design of Flotation Circuits Using Tabu-Search Algorithms: Multispecies, Equipment Design, and Profitability Parameters

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