基于混合遗传—蚁群算法的MRO服务调度研究

Study on MRO service scheduling based on hybrid genetic algorithm-ant colony optimization

随着设备的维修、维护和大修(maintenance,repair&overhaul,MRO)规模扩大,设备的维修和维护越来越难,成本越来越高,MRO服务企业需要更加科学合理地调配资源,这就带来了MRO服务调度问题。为此提出了一种基于混合遗传—蚁群算法的MRO调度方法。建立了维修服务调度问题数学模型,采用混合遗传—蚁群算法对模型求解,以综合适应值最小为优化目标,得出最优调度方案,解决了MRO服务调度问题。最后,以某航天企业的10个维修任务为例,比较了提出的基于混合遗传—蚁群算法的调度方法与常规遗传算法、蚁群算法的优化结果,结果表明两种算法结果一致,且基于遗传—蚁群算法的调度方法收敛速度更快,从而验证了本方法的可行性。

This paper proposed a novel hybrid genetic algorithm （GA）-ant colony optimization （ACO） method to solve the problem of scheduling of MRO service. The ACO method could establish the model and obtain the optimal scheduling scheme by the minimum comprehensive fitness as the optimization goal, and solved the contradiction of maintenance time and mainte- nance cost of MRO. Finally, as a validation, it used a 10 actual maintenance tasks of an aerospace enterprise to validate the validity of the proposed arithmetic. The result shows that the proposed hybrid GA-ACO method has a faster convergence speed, so it validates the maneuverability and feasibility of the proposed method.