Coal consumption modeling of heat-setting process and its solution with improved Genetic Algorithm

Based on heat balance and Newton´s heat exchange formula, energy consumption model of heat-setting process is established. Next, according to the requirements of heat-setting process, an improved Multi-Constrained Condition Adaptive Genetic Algorithm (MCC_AGA) was proposed. The suggested algorithm has made two improvements: effectively dealing with multi-constrained conditions using different strategies; and introducing multi-levels self adaptive genetic operators. Finally MCC_AGA optimization method has been applied in solving the heating-setting energy consumption model. The simulation results of real industrial data show the suggested MGG_AGA algorithm has faster and better optimization performances. The energy consumption model and the MGG_AGA optimization algorithm could provide industrial engineers some good suggestions to decrease the process´s coal consumption and improve their operations of the heat-setting machine.