Abstract

Traditional research on sintering burdening focuses on adjusting proportion of different ore and other raw materials to optimize certain objective functions that are defined in term of material costs. With regard to environmental concerns, energy consumption becomes another critical issue in sintering burdening. A collaborative optimization model is proposed to integrate the energy performance and physical index into the optimization of sintering burdening in this paper. Firstly, the collaborative optimization problem in sintering burdening is generally described, and then the association models between sintering raw material proportion, production parameters and energy consumption, drum index are established using data-based methods. Meanwhile, the future production parameters are predicted by GM(1,1) method. After that, objective functions and constraints of the collaborative optimization model are formulated based on the association models. After model reduction, two case studies derived from a large-scale iron and steel enterprise are investigated. The results show that the association models can describe the relationship effectively. Meanwhile, Energy performance was optimized with production constraints satisfied, and there is a trade-off between cost and energy consumption.

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