Optimal operating conditions for the primary end of an integrated steel plant: genetic adaptive search and classical techniques

Abstract

The optimal operating conditions for the primary end of an integrated steel plant, which essentially comprises of sintering plant, pelletizing plant, blast furnaces, oxygen steelmaking converters and electric arc furnace, are found through a modern technique of optimization, namely, genetic adaptive search (GAS), and also through classical techniques of simplex search with simulated annealing (ASM) and sequential quadratic programming (SQP). A comparison of these techniques shows that GAS outperforms both the classical methods and obtains the lowest cost solution. Based on this study, it is recommended that GAS be used, in preference to other methods, in complex steel plant optimization problems.