Dual multi-objective optimisation of the cane milling process

Abstract

Sucrose extraction and energy consumption form the basis for evaluating the performance and energy efficiency of milling. Herein a double-layer multi-objective optimisation method was proposed for optimising the sugarcane crushing process. The MIV-MOPSO-KELM is proposed to model the objective function, and the high accuracy and stability of the prediction model are ensured. Monitoring and laboratory data obtained from a sugar factory in China were used as examples to conduct an empirical analysis. The results showed that the model performed well in predicting the energy consumption and sucrose extraction. Finally, the TOPSISdecision-making technique based on entropy weight was employed to undertake multi-objective decision-making. The results show that the proposed double-layer multi-objective optimisation method effectively optimises multi-factor, multi-objective, and nonlinear milling process. This new solution provides a basis for further research on the optimisation control of the sugarcane milling process.