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为了将决策者的偏好综合到多目标问题求解过程中,提出了一种偏好多目标蜂群优化算法PMABCA.在PM ABCA中,给出了一种新的偏好距离计算方法,基于非支配等级与偏好距离定义了适应度分配函数,并引入了归档集用于非支配解的存储.为了清除非支配集中多余的解,提出了改进的偏好拥挤距离算子.针对经典函数优化问题的计算结果表明,PMABCA可以在输出完整Pareto前端的基础上,确保输出大量符合偏好的最优解.将PMABCA应用于过热汽温控制系统PID参数优化问题,仿真结果表明,新算法的结果更便于决策者做出合理决策.
In order to integrate decision-maker’s preferences into the multi-objective problem solving process, a preference multi-objective bee colony optimization algorithm PMABCA is proposed. In PM ABCA, a new preference distance calculation method is proposed based on non-dominated ratings and The preference distance defines the fitness distribution function, and introduces the archive set for the storage of the non-dominated solution.In order to eliminate the nonconvergent centralized redundant solution, an improved preference crowding distance operator is proposed. The calculation results for the classical function optimization problem , PMABCA can ensure the output of a large number of optimal solutions based on the output Pareto front.PMABCA is applied to PID parameter optimization of superheated steam temperature control system.The simulation results show that the new algorithm is more effective for decision makers to make Reasonable decision-making.