A hybrid genetic algorithm for byproduct gas scheduling in steel plant

Byproduct gas is an important secondary energy in steel plant, and the reasonable use of byproduct gas has a great significance. For the byproduct gas real-time scheduling problem in a steel plant in China, a hybrid genetic algorithm based scheduling method is proposed in this study. First, this method takes into account the differences of the scheduling units of gas consumption and the nonlinear relationship between the production and consumption of each unit and the gas tanks. Second, an optimal scheduling model is established to minimize the production cost. And, the proposed hybrid genetic algorithm changes the constrained programming into an unconstrained programming. At last, the experiments employing the real world industrial data based on the two cases of blast furnace gas counters overrun and insufficiency verify the effectiveness of the proposed hybrid genetic scheduling algorithm on the gas system by comparing with some other algorithms.