Prediction, parametric analysis and bi-objective optimization of waste heat utilization in sinter cooling bed using evolutionary algorithm
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- @Article{Liu:2015:Energy,
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author = "Yan Liu and Jian Yang and Jing-yu Wang and
Xu-gang Ding and Zhi-long Cheng and Qiu-wang Wang",
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title = "Prediction, parametric analysis and bi-objective
optimization of waste heat utilization in sinter
cooling bed using evolutionary algorithm",
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journal = "Energy",
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volume = "90, Part 1",
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pages = "24--35",
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year = "2015",
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ISSN = "0360-5442",
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DOI = "doi:10.1016/j.energy.2015.05.120",
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URL = "http://www.sciencedirect.com/science/article/pii/S0360544215007422",
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abstract = "Based on our previous work, the AEGs (annual energy
gains) could be obtained on energy and exergy analysis
for a sinter cooling bed. In the present study, a
method synthesizing both economic cost and energy
benefit aspects of the sinter cooling bed is proposed.
Firstly, the GP (genetic programming) is employed to
derive accurate correlations between the AEGs and
operational parameters. Then, the economic cost model
is established to evaluate effects of operational and
economic parameters on the EAOC (equivalent annual
operational cost). Finally, bi-objective optimization
of the sinter cooling bed is performed to achieve the
optimal operational conditions from both waste heat use
and economic cost aspects using NSGA-II (non-dominated
sorting genetic algorithm-II). In order to maximize the
AEGs and minimize the EAOC, the EAOC and the AEGs based
on the first and second laws of thermodynamics are
selected as two objective functions. A Pareto frontier
obtained shows that an increase in the AEGs can
increase the EAOC of the sinter cooling bed. Under the
given operational conditions, the optimum solutions
with their corresponding decision variables are
obtained. After considering both two Pareto frontiers
curves, a set of suggested operational parameters for
the decision-makers is also obtained.",
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keywords = "genetic algorithms, genetic programming, Sinter
cooling bed, Waste heat recovery, Bi-objective
optimization",
- }
Genetic Programming entries for
Fiona Yan Liu
Jian Yang
Jing-yu Wang
Xu-gang Ding
Zhi-long Cheng
Qiu-wang Wang
Citations