A BC-PSO algorithm of multi-objective and fuzzy satisfactory optimization for sintering burden

Considering the characteristics of sintering burden process and the requirements of energy-saving and environment protection for iron and steel industry. This paper presents a multi-objective optimization algorithm based on fuzzy satisfaction. Firstly, the fuzzy satisfactory functions that can describe the actual satisfaction about the cost and sulfur contained are built, and then a multi-objective optimization model is established in which cost and emission is considered to maximize the minimum satisfaction degree. Secondly, for the nonlinear and multivariable features of this model, a BC-PSO algorithm is proposed by combining the extensive mapping ability of particle swarm optimization (PSO) algorithm and the strong local search ability of bee colony (BC) algorithm. The practical data based simulation indicates that the BC-PSO algorithm can work efficiently on cost decreasing and emission reduction.