Use of genetic algorithm for determination of parameters in langmuir isotherm in the system metal ions-electric furnace slag

In this paper, sorption of Pb2+ and Cu2+ ions in the single-metal system has been studied using electric furnace slag (EFS), a by-product from Felis foundry in Sisak, Croatia, and batch techniques. The influence of the initial concentration of Pb2+ and Cu2+ and the temperature at which the sorption takes place has been studied. The experimental results showed that Cu2+ and Pb2+ could be effectively removed by sorption on EFS. Sorption isotherms obtained from equilibrium data were fitted and interpreted by the Langmuir model. The Langmuir model is widely used since it is simple and has the ability to describe experimental results in a wide range of concentrations. Langmuir isotherm model can be easily transformed into linear forms to obtain adjustable parameters just by graphical means or by linear regression analysis. The aim of this work is to make a comparison of determination of parameters in Langmuir isotherm by using linear regression analysis (LRA) and genetic algorithm (GA). Each method of determination of parameters in Langmuir isotherm was evaluated by calculating the mean value of the residual sum of squares (RSS) and the mean square errors (MSE). Langmuir isotherm parameters obtaining by genetic algorithm showed better fitting with experimental results.