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Dynamic optimization based on state transition algorithm for copper removal process

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Abstract

The copper removal process (CRP) is an indispensable step for the purification of zinc sulfate solution by adding powdered zinc to a series of reactors in zinc hydrometallurgy. The selection of optimal amount of zinc powder is a complicated task because of the complex reaction mechanism, resulting in the fluctuation of copper ion concentration and the waste of zinc powder in the actual process. In this paper, we formulate a dynamic optimization problem (DOP) for the control of the zinc powder in CRP, aiming at reducing production costs and improving product quality simultaneously. A novel dynamic optimization method based on the state transition algorithm (STA) is investigated for solving this problem, and to improve the performance of STA, an adaptive strategy is adopted by its transformation operators. Simulation results from some classical DOPs show that the proposed method can optimize effectively and efficiently. The proposed approach is successfully applied to solve the DOP arising in CRP and the simulation results show that zinc powder consumption is considerably reduced under the assumption of an acceptable copper ion concentration.

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Acknowledgements

Authors thank the National Natural Science Foundation of China (Grant Nos. 61503416, 61533020, 61533021, 61590921), the 111 Project (Grant No. B17048), National Priority Research Project NPRP 8-274-2-107, funded by Qatar National Research Fund and the Fundamental Research Funds for the Central Universities of Central South University (Grant No. 2017zzts487) for the funding support.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, 410083, China

    Miao Huang, Xiaojun Zhou, Chunhua Yang & Weihua Gui

  2. Texas A&M University at Qatar, Doha, 23874, Qatar

    Tingwen Huang

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  1. Miao Huang
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  2. Xiaojun Zhou
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  3. Tingwen Huang
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  4. Chunhua Yang
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  5. Weihua Gui
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Correspondence to Xiaojun Zhou.

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Huang, M., Zhou, X., Huang, T. et al. Dynamic optimization based on state transition algorithm for copper removal process. Neural Comput & Applic 31, 2827–2839 (2019). https://doi.org/10.1007/s00521-017-3232-0

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  • DOI: https://doi.org/10.1007/s00521-017-3232-0

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