The application of multi-objective differential evolution algorithm in the combustion process of coke oven

For the setting controller parameter by artificial experience can´t adapt to the complex condition of combustion process of coke oven, this paper presents a multi-objective optimization model to minimize the flue temperature deviation, the flue temperature mean-square deviation and settling time. The paper presents an improved multi-objective differential evolution algorithm for the combustion process of coke oven optimization. Introducing chaotic initialization strategies based on Tent map, we can improve the diversity of the initialized population. Computing the non-inferior level and the crowding distance of the genes, we can the Pareto solutions of the multi-objective problems. Based on the heat output model, we develop the mechanism model of the combustion process of coke oven. Simulations verified the effectiveness of the method.