Dynamic optimization based on state transition algorithm for copper removal process

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 i...

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Vydáno v:Neural computing & applications Ročník 31; číslo 7; s. 2827 - 2839
Hlavní autoři: Huang, Miao, Zhou, Xiaojun, Huang, Tingwen, Yang, Chunhua, Gui, Weihua
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Springer London 01.07.2019
Springer Nature B.V
Témata:
Algorithms
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer simulation
Copper
Data Mining and Knowledge Discovery
Hydrometallurgy
Image Processing and Computer Vision
Ion concentration
Optimization
Original Article
Performance enhancement
Probability and Statistics in Computer Science
Production costs
Reaction mechanisms
Variations
Zinc
Global optimization
State transition algorithm
Copper removal process
Dynamic optimization
ISSN:0941-0643, 1433-3058
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Shrnutí: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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ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-017-3232-0