Based on the characteristics of gasoline blending optimization

an active constraints aided objective method was proposed. Active constraints were distinguished by the feasible solutions and infeasible solutions in the population of an evolutionary algorithm. With these active constraints

an active constraints aided objective was added to the gasoline blending optimization and the problem was transformed into a multi-objective constrained optimization problem.  This method incorporated the knowledge of active constraints into the selection operation of the evolutionary algorithm to improve its selection efficiency and guide its search away from local optima. The application of the strategy was demonstrated by a case study.