A vertical layered cooling process is developed to get more uniform cooling and higher heat transfer efficiency when compared with the circular-type and vertical integrated sinter cooling processes in this work, which has been demonstrated by the example. Based on the vertical layered cooling process, the maximum temperature of the cooled sinter and the minimum waste heat recovery is treated as two objective parameters for the multi-objective optimization design. The operating parameters influencing the sinter temperature and waste heat recovery are determined at first. Then, an accurate metamodel is established based on the Latin hypercube sampling technique and radial basis function neural network (RBFNN) approach. Finally, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to iterate the accurate metamodel and acquire the Pareto frontier for acquiring the optimal combinations of the objective parameters. Analysis results are demonstrated to be of great significance for practical engineering applications.
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