Gasoline blending recipe optimization based on twoparticle swarms optimization
As an important procedure of the manufacturing process in refinery, oil blending could be abstracted as a complex non-linear optimization problem (NLP) with many constraints.It is difficult to obtain satisfying optimum solution by traditional methods.According to the oil blending and scheduling problem, a two particle swarms optimization algorithm with a mutation operator was presented.The proposed algorithm constructed two swarms of particles with different velocity restrictions, introduced a communication mechanism and a special mutation operator, and sequentially elevated the swarms to higher ability and velocity of global convergence.The new method was illustrated with a recipe optimization problem of gasoline blending, and the feasibility and effectiveness of the proposed algorithm was experimentally confirmed by the simulation results.