Aiming at the limitation that the single-objective optimizing algorithm is generally easy to trap into local optimal solution

multi-objective evolutionary algorithm based on elitist selection and individual migration was proposed for single-objective optimization problem.Decomposing the original single objective into multi-objectives

it could broaden its searching extension and quicken its converging speed.Simulation results showed that the proposed method could obviously speed up its converging performance.Furthermore

the application to p-xylene oxidation reaction indicated that the proposed method could obviously reduce acetic acid and p-xylene combustion loss

greatly reduce production cost at the same numerical computing cost.