关键词:

微粒群算法, 油品调和, 配方优化

Abstract:

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.

Key words:

微粒群算法, 油品调和, 配方优化