A hybrid gene algorithm for mixed byproduct gas scheduling in iron and steel production

This paper concentrates on the mixed byproduct gases scheduling (MBGS) problem in iron and steel enterprises. The units in a typical MBGS system are categorized into five types, whose features are discussed. Then a MILP mathematical model is built to minimize the excess and the shortage of gas distribution. A hybrid algorithm combined gene algorithm (GA) and linear programming (LP) is presented based on benders decomposition and a method of double- two- stages (DTS) proposed to solve the problem. The computational tests show that the proposed hybrid algorithm is practically effective.